Appendix B: State Estimation Methodology

B.2 Validation

The validation study was performed by pairing the eight large sample States to form design-based benchmark estimates based on samples of around 7,200 respondents per year. For each of these State pairs, eight sample replicates were formed that mimicked the overlapping of sample segments in the 1999 and 2000 surveys from 1 of the 43 small sample States. A key feature of this replicate formation strategy was mimicking the 50 percent overlap between the samples of 96 area segments surveyed in 1999 and 2000 in a small sample State. Because new samples of dwellings and persons were drawn from all sample segments for the 2000 NHSDA, the survey design-induced covariance between years is limited to this 50 percent overlap of sample block groups/segments.

B.2.1 Introduction

To validate the fit of the 1999 NHSDA SAE models, the eight large sample States had been used as internal benchmarks. For this purpose, 12 pseudo field interviewer (FI) regions had been created within each large sample State by pooling the 48 initial regions into groups of four. Each of these pseudo FI regions were then expected to have eight area segments per calendar quarter. For each of these pseudo FI region-by-quarter sets of eight area segments, any segments devoid of interviews were first randomly replaced by a selection from the non-empty segments in the set. The completed set of eight segments from each pseudo FI region-by-quarter combination was then randomly partitioned into four replicates of two segments each. Combined across the 12 pseudo FI regions and the four calendar quarters, each of the four substate replicates mimicked the size and design structure of a small State sample.

Having created four pseudo small State samples and associated universe-level files for each large State, SAEs were then produced for 75 States (43 + 32), which included the 42 small States and the District of Columbia and the 32 substate territories defined across the eight large sample States. To validate the SAE models, the 32 pseudo small State SAEs were compared with the corresponding large State design-based estimates.

Commenting on the 1999 validation study, William Bell, a member of the panel of SAE advisors (see Section B.6.1), noted that the design-based estimates from a single large State were probably not precise enough to serve as an internal benchmarks because a large State sample size is only 4 times larger than a small State sample size. Therefore, to provide more precise internal benchmarks for the 2000 NHSDA SAE model validation, the eight large States were grouped into four pairs. The SAE model validation methodology used for the 2000 NHSDA is described in the next section.

B.2.2 Subsampling Pairs of States

To validate the prevalence (level) estimates produced by the 2000 SAE models and the associated measures of change between the 1999 and 2000 SAE estimates, the eight large sample States were grouped into four pairs: (a) California and Texas, (b) New York and Florida, (c) Ohio and Michigan, and (d) Pennsylvania and Illinois. This represented an improvement over the 1999 validation design in that the design-based estimates for individual large States had been somewhat imprecise to serve as internal benchmarks (the estimated unbiased "true" value) for the small State SAEs. The large State sample sizes were only approximately 4 times larger than the small State sample sizes. By grouping the eight large sample States into four pairs, the individual design-based estimate for each pair was based on a sample that was now 8 times as large as that for a small State. These pairs were formed based on State population totals so as to minimize variance inflation in the design-based estimates for the State pairs that results from unequal weighting. The design-based estimates corresponding to the four pairs were used as internal benchmarks.

To select the eight pseudo small State samples from each large State pair, six pseudo FI regions were first created within both of the paired large sample States by pooling their 48 initial regions into groups of eight. Each of these pseudo FI regions was then expected to have 16 area segments per calendar quarter. For each of these pseudo FI region-by-quarter sets of 16 area segments, any segments that were devoid of interviews were first randomly replaced by a selection from the non-empty segments in the set. The segments for the 1999 and 2000 NHSDA data were filled in separately. Once complete sets of 16 non-empty segments for the 1999 and 2000 NHSDA data in each of the pseudo FI region by quarter sets were assembled, the 1999 and 2000 data were linked using State-by-pseudo FI region-by-quarter-by segment identification codes. Approximately half of the 16 segments represented cases where the 1999 segments were reused in 2000 (i.e., common segments in 1999 and 2000), and the remaining ones represented cases where a 1999 segment was linked with a new 2000 replacement segment. Next, the 16 linked 1999 and 2000 segment pairs were stratified into two strata—the common segment pairs and the uncommon 1999 and 2000 segment pairs. One segment pair was then drawn from each of these strata and combined to form eight replicate pairs such that one of the paired replicates would have common segments in the 1999 and 2000 surveys and the other replicate pair would have uncommon segments for 1999 and 2000.

This subsampling validation exercise was repeated for all four quarters in a pseudo FI region, for all six pseudo FI regions in both States of the pair, and for all four pairs of large States. This resulted in 32 (4 large State pairs × 8 subsamples from each large State pair) replicate subsamples from four large State pairs. These subsamples mimicked the design properties of small States. For example, let CA_TX1 represent the first subsample from the California and Texas pair. Then subsample State CA_TX1 will have 12 pseudo FI regions (six from California and six from Texas), each pseudo FI region will have four quarters, and each quarter will have two segments per survey year. Of these two 1999 segments, one segment would be retained in the 2000 survey and the other 1999 segment would be replaced. This was desirable because one of the goals was to estimate the change in drug use prevalence rates between 1999 and 2000. The planned 50 percent overlap in sample segments between the 1999 and 2000 surveys would be expected to yield positive between-year correlations and reduced posterior variances for the change measures. Survey weights for the eight subsamples formed from each large State pair were appropriately scaled so that their totals over the subsamples would reproduce the age-group-level large State pair totals.

Having created eight pseudo small State samples and associated universe-level files for each large State pair, SAEs for the models described in the following section were then produced for 75 States, which include the 42 small States and the District of Columbia and the 32 substate territories defined for each large sample State.

B.2.3 Results of SAE Models of Prevalence Levels

Table B.1, provided at the end of this appendix, compares Model 1 estimates of the prevalence levels for 2000 to the "true" design-based estimates for each of the four substances estimated in the validation. A "Model 1 estimate" is the mean over the eight substates of the prevalence estimates. As shorthand, Model 1 estimates of the prevalence level for 2000 have been denoted as P1. The P1 estimates are generally quite close to the design-based estimates for each of the large State sample pairs, for each of the age categories, and across all four substances measured.

Table s B.2 to B.5 present the means over the eight substates for the three types of SAEs mentioned above. The paired large State design-based estimates are also included for comparison purposes. The RABs are shown in these tables, including the average RABs over the four pairs of large States. Overall averages of these RABs across the four outcome variables are presented in Table B.6.

Focusing on just the 12 or older age group, the overall RABs are quite small, ranging from a low of about 1 percent (for past month cigarette use) to 6 percent (for past year cocaine and past month marijuana use). This is similar to the results for 1999.

The three point estimates (P1, P2, and P3) surprisingly gave similar results, with none consistently superior over the four substances. The overall RAB averages for the 26 or older age group and the total appear to be lowest for P1.

Table B.7 shows averages over eight substates of the 95 percent lower and upper prediction interval (PI) bounds of P1 for the four outcome variables. The corresponding paired large State design-based 95 percent confidence interval (CI) bounds are also included for comparison purposes to the model-based 95 percent PIs. It should be noted that the design-based intervals of the paired large States are typically smaller owing to the larger sample sizes of approximately 6,000 to 8,000 cases for the 12 or older age group. Table B.8 shows ratios of average widths of 95 percent PIs for the model-based estimates divided by the corresponding averaged design-based interval widths for the eight substate replicates (denoted W1, W2, and W3 to correspond to estimators P1, P2, and P3, respectively). Here, the model-based estimates mimic the design and hierarchical Bayes estimation of the 42 small States and the District of Columbia, with each substate replicate having a sample of approximately 900 total for the 12 or older age group. The overall average shows that the model-based PIs were 25 to 35 percent shorter than the design-based CIs. The largest reduction in width occurred for the P1 PIs.

B.3 Conclusions about Measuring Change

The information provided in Sections B.1 and B.2 was also provided to the expert panel on SAE for its review. The panel's consensus was that the NHSDA should not be used to measure change between 1999 and 2000. Instead, the panel indicated that the Substance Abuse and Mental Health Services Administration (SAMHSA) would be better served by providing improved estimates of the prevalence levels based on combining the 1999 and 2000 data while exploring other possibilities for measuring change for 2001.

Several options for measuring change were discussed:

1. Calculate a 2-year moving average to increase the precision of estimated change. Change then would be measured as the difference between two consecutive 2-year moving averages (e.g., the combined 2000-2001 moving average minus the combined 1999-2000 moving average).
2. Jointly model two related variables at one time to increase the precision of the individual yearly estimates, thereby increasing the precision of year-to-year change.
3. Create a "100 percent overlap" by asking the respondent to provide retrospective information for the "year before last" as well as for the past year.
4. Using the current 50 percent overlap of segments, reinterview respondents in those segments in 2 consecutive years.
5. Encourage the Center for Substance Abuse Prevention (CSAP) and the Center for Substance Abuse Treatment (CSAT) to have States institute annual data collection of variables that are related to program participation and success and are based on consistent definitions across States.

For each option, the SAE expert panel discussed the advantages and disadvantages. The advantages were typically either a shorter time frame for implementation or a greater potential for significant improvement in precision. Results of the discussion are summarized below.

Option 1 is the only short-term solution that could be used in 2001. The variance of a difference of two 2-year moving averages is one quarter of the variance of a difference of 2 consecutive years. This is a significant improvement; however, it still may not be possible to detect change for some measures in many States. There is a better opportunity among those States for which the trend between 1999 and 2001 continued in the same direction (either positive or negative).

Option 2 could be implemented in about 1 year and used to complement the other options in order to give added improvement to the precision of the change estimates. This option may require significant reprogramming implementation costs. The primary impact of this multivariate approach is the improved estimation of prevalence levels; however, this will also carry over to better estimation of yearly change and better correlation between years. The NHSDA data can be used to estimate the potential improvement resulting from its implementation. Some of the possible estimates that could be used together include modeling past month marijuana use and past month use of any illicit drug simultaneously, modeling past month use of a substance with past year use of the same substance, and modeling past month use of a substance with a scale based on risk factors.

Option 3 is believed to have potential; however, there can be problems because of memory recall decay. It may be best considered in conjunction with Option 2 in that retrospective data can be modeled jointly with the main outcome to improve precision. Various methods of adjusting for potential memory recall problems were considered. Data have been collected from earlier NHSDAs that may allow the estimation of potential gain under different alternatives relating to the size of the year-to-year correlation, depending on whether the recency measure is past month, past year, or some other reference period. This method would not be applicable to measures of perceived risk (asking a retrospective question about perceptions over a year ago) or to measures based on a series of questions, such as past year dependence.

A significant difficulty with Option 4 is that it represents a major departure from current data collection protocol with respect to confidentiality and follow-up. This would probably mean that other options would be pursued before this was given greater consideration. The NHSDA has typically been presented as an annual survey that does not reinterview individuals and only maintains the household address and selected respondent identification for quality verification follow-up. There is also the issue of nonresponse, especially in the reinterview. The $30 incentive would probably ameliorate the nonresponse problem to some extent.

Option 5 is more of a long-range goal. Its viability depends on adherence to consistent definitions and its ultimate predictive ability, which cannot be known in advance. Both CSAP and CSAT obtain State-level data, but the collection is typically not annual and often does not cover all 50 States and the District of Columbia.

The SAE experts suggested first conducting research based on available data and utilizing "off-the-shelf" software to better understand the potential gains that might be achievable.

B.4 Modeling Estimates Based on Combining Data from 1999 and 2000

B.4.1 Modeling Without the Region Main Effect

In addition to combining 2 years of data for the next set of State estimates, another concern was the potential impact on individual States within each region of including Census region in the model, as had been done for the 1999 State small area estimates. The concern was that the presence of a significant regional fixed effect would have an automatic result of raising or lowering the measure of substance use for each State in the region regardless of whether a given State followed the regional pattern or not. In addition to providing the best fit of the data for the States and the District of Columbia collectively, one of the primary goals was to distinguish real differences among States. Thus, including a fixed regional effect seemed counterintuitive. Although the regional effect could come collectively from a set of States in a region, it was also a concern that a single State having a relatively large population relative to the region (e.g., California in the West) could have a significant effect on the remaining States in the region, especially if its substance use level were significantly different.

To compare the impact of including versus excluding the region variable main effects, models were fit on a handful of substance use measures for the two alternatives using the SAE methodology. In addition to the region main effects, it was decided that any interactions of region with race/ethnicity or gender needed to be excluded as well because their effect on States within a region would be similar. The interactions of all other variables with region (e.g., the percentage of single mothers in the Census tract) were left in the model because differential State distributions of that data would still result in differential impacts among States within the same region.

Results are presented for four of the substances. The interest here was in comparing the average behavior across States of the two different models. Table B.18 displays the design-based estimates and SAE estimates for past month use of marijuana with region and without region. Table B.19 displays similar information for past year use of cocaine. Table s B.20 and B.21 display similar information for past month use of alcohol and past month use of cigarettes, respectively.

The estimates for past month use of marijuana for persons aged 12 or older showed that the average State differences between the SAE estimates and the design-based estimates were very similar—0.07 percent for the model without region and 0.11 percent for the model with region (Table B.18). The width of the 95 percent PIs also was similar—1.98 and 1.95 percent for the models without and with region, respectively. Also, the with-region estimate for Utah, a State that typically displays significantly lower prevalence rates than the remainder of the West region, was 0.58 percentage points higher than the design-based estimate, while the without-region estimate was only 0.14 percentage points higher.

A comparison of the estimates for alcohol use shows that the national SAE estimates were almost identical for the two models, and the difference from the national design-based estimate was only a quarter of a percent. The average difference across States between the model without region and the design-based estimate for those aged 12 or older was -0.44 percent, and the average absolute difference was 1.00 percent (Table B.20). For the model with region, the corresponding averages were -0.39 and 0.97 percent. The average PI widths were 6.26 percent for the model without region and 6.02 percent for the model with region. Thus, for example, a State such a Utah that displayed a much lower level of past month use of alcohol than other States in the West had a with-region SAE that was 3.20 percentage points higher than the corresponding design-based estimate and a without-region SAE that was only 1.92 percentage points higher.

In addition to these comparisons, the SAE estimates were validated for another substance, "the treatment gap rate" (not shown in tables) using the four large-State design-based estimates as the "true" value. The results showed that the SAE estimates for the without-region model were very close to the corresponding "true" values.

B.4.2 Validation of the SAE for the Combined 1999 and 2000 Data

Given that the decision had been made to produce SAE estimates based on combining 2 years of data, the next step was to produce those estimates for each of the substance measures for which there were 2 years of data and validate the estimates using the model that excluded any regional main effects and interactions, as described in Section B.4.1.

The 2-year estimates were validated on four variables: past month use of marijuana, past year use of cocaine, past month "binge" alcohol use, and past month use of cigarettes. For this validation exercise, large States were not combined. Each large State was divided into four substates. The results are presented in Table s B.22 to B.25. On average, the RABs were quite small. For the 12 or older age group, the RABs were as follows:

• past month use of marijuana, 4.07 percent;
• past year use of cocaine, 7.88 percent;
• past month "binge" alcohol use, 0.98 percent; and
• past month use of cigarettes, 1.22 percent.

Also, compared with the design-based CIs, the 95 percent PIs were much shorter, about 75 percent as large for marijuana, "binge" alcohol, and cigarettes and 65 percent as large for cocaine (Table B.26).

In addition, the 2-year estimates were compared with the corresponding 1-year estimates to ascertain the extent of improvement in estimation for the 42 States and the District of Columbia, given that those sample sizes would now be approximately double their size in 1999. For example, comparing the PIs' widths across the 50 States and the District of Columbia, the average SAE PI width for past month use of marijuana among persons 12 or older was 2.40 percent in 1999, but only 1.98 percent for 1999 and 2000 combined. Just as importantly, because the States (and the District of Columbia) had smaller single-year sample sizes, the national model had a greater relative influence in the SAE estimates for 1999 than for 1999 and 2000 combined. Therefore, the 1999-2000 pooled State estimates would not be shrunk as much toward the national model-based estimate as would similar estimates based on a single year of data. One result is that the 2-year SAEs would tend to be closer to their corresponding design-based estimates than SAEs based on 1 year of data. The other implication is that States with design-based estimates that were relatively lower or higher than other States would retain that distinction, and the overall range and spread of the State estimates would tend to be larger, for example, than it was in 1999. This should make it easier to identify States that have significantly lower or higher substance use prevalence rates than other States.

B.5 Caveats

Most of the caveats regarding SAE, including differential nonresponse and response bias effects, are addressed in Chapter 6 of this report. Table s B.27 and B.28 show the screening and interview response rates for the 50 States and the District of Columbia in 1999 and 2000, respectively. One other possible contributor to bias in the State estimates, and the estimates in general, is the effect of editing and imputation of the summary data. In developing the editing and imputation process for 1999 and subsequent years, the desire was to minimize the amount of editing because of its somewhat subjective nature, and instead let the random imputation process supply any partially missing information. Overall, the percentage of imputed information is quite small for any given substance.

The method described in Appendix D is based on a multivariate imputation in which some demographic and other substance use information from the respondent is used to determine a donor who is similar in those characteristics but has supplied data for the drug in question. Often, information is also available from the partial respondent on the recency of drug use. For example, respondents may have indicated that they used the drug in their lifetime or in the past year, but left blank the question about use in the past month. For many of the records, this type of auxiliary information was available. In a small portion of the time, no auxiliary information was available, in which case a random donor with similar drug use patterns and demographic characteristics was used. For the different substances, the largest differences between the edited and the imputed estimates typically occurred when there was a lot of auxiliary information. For past month use of marijuana, based on the 1999 data, the State with the largest percentage change from edited to imputed data was Alabama, whose edited rate of use of marijuana was 2.1 percent and whose imputed rate of use was 3.1 percent—a relative increase of almost 50 percent.

B.6 SAE Methodology

B.6.1 Background

In response to the need for State-level information on substance abuse problems, SAMHSA began developing and testing SAE methods for the NHSDA in 1994 under a contract with RTI of Research Triangle Park, North Carolina. That developmental work used logistic regression models with data from the combined 1991 to 1993 NHSDAs and local area indicators, such as drug-related arrests, alcohol-related death rates, and block group/tract level characteristics from the 1990 Census that were found to be associated with substance abuse. In 1996, the results were published for 25 States for which there were sufficient sample data (OAS, 1996). A subsequent report described the methodology in detail and noted areas in which improvements were needed (Folsom & Judkins, 1997).

The increasing need for State-level estimates of substance use led to the decision to expand the NHSDA to provide estimates for all 50 States and the District of Columbia on an annual basis beginning in 1999. It was determined that, with the use of modeling similar to that used with the 1991 to 1993 NHSDA data in conjunction with a sample designed for State-level estimation, a sample of about 67,500 persons would be sufficient to make reasonably precise estimates.

The State-based NHSDA sample design implemented in 1999 and 2000 had the following characteristics:

• States were stratified into FI regions that covered the geography of each State. The FI regions are comprised of contiguous Census tracts and counties and designed to yield about 75 interviews per region. In the 42 smaller States (by population) and the District of Columbia, there are 12 FI regions; in the eight large States, there are 48 FI regions.
• Within each region, eight segments were randomly selected for 1999 and two were allocated to each calendar quarter of data collection. For 2000, one segment from each 1999 region by quarter pair was retained, and its partner was replaced by a new random selection.
• Within each segment, households were screened, and a sample of one to two persons per household was selected. An average of nine responding persons per segment was sought. For the 1999 segments that were retained in 2000, a new sample of households and persons was drawn for the 2000 survey.
• The annual samples were selected so that approximately 900 responding persons, 300 in each age group (12 to 17, 18 to 25, and 26 or older), were drawn in each of the 42 States and the District of Columbia. In the eight large States, the person samples were allocated equally to the three age groups with overall respondent sample sizes ranging from 2,669 to 4,681 in 1999 and 3,478 to 5,022 in 2000.

In preparation for the modeling of the 1999 data, RTI used the data from the combined 1994-1996 NHSDAs to develop an improved methodology that utilized more local area data and produced better estimates of the accuracy of the State estimates (Folsom, Shah, & Vaish, 1999). That effort involved the development of procedures that would validate the results for geographic areas with large samples. This work was reviewed by a panel with SAE expertise.² They approved of the methodology, but suggested further improvements for the modeling to be used to produce the 1999 State estimates. Those improvements were incorporated into the methodology finally used for the 1999 State estimates. Similar methodology (as described earlier) was used for this 2000 State report. The methodology, called Survey-Weighted Hierarchical Bayes Estimation (HB), is described below.

B.6.2 Goals of Modeling

There were several goals underlying the estimation process. The first was to model drug use at the lowest possible level and aggregate over the levels to form the State estimates. The chosen level of aggregation was the 32 age group (12 to 17, 18 to 25, 26 to 34, 35+) by race/ethnicity (white, non-Hispanic; black, non-Hispanic; Hispanic; Other) by gender cells at the block group level. Estimated population counts were obtained from a private vendor for each block group for each of the 32 cells. This level of aggregation was desired because the NHSDA first stage of sample selection was at the block group level, so that there would be data at this level to fit a model. In addition, there was a great deal of information from the Census at the block group level that could be used as predictors in the models. If prevalence rates could be estimated for each of the 32 cells at the block group level, it would only be necessary to multiply by the estimated population counts and aggregate to the State level.

Another goal of the estimation process was to include the sampling weight in the model in such a way that the small area estimates would converge to the design-based (sample-weighted) estimates when they were aggregated to a sufficient sample size. There was a desire for the estimates to have this characteristic so that there would be consistency with the survey-weighted national estimates based on the entire sample.

A third goal was to include as much local source data as possible, especially data related to each substance use measure. This would help provide a better fit beyond the strictly sociodemographic information. The desire was to use national sources of these data so that there would be consistency of collection and estimation methodology across States.

Recognizing that estimates based solely on these "fixed" effects would not reflect differences across States due to differences in laws, enforcement activities, advertising campaigns, outreach activities, and other such unique State contributions, a fourth goal was to include "random" effects to compensate for these differences. The types of random effects that could be supported by the NHSDA data were a function of the size of sample and the model fit to the sample data. Random effects were included at the State level and for substate regions comprised of three neighboring FI regions. Although this grouping of the three FI regions was principally motivated by the need to accumulate enough sample to support good model fitting for the low prevalence NHSDA outcomes, it was also reasoned that it would be possible to produce substate HB estimates for areas comprised of these FI region groups, once 2 or 3 years of NHSDA data were available, because that would yield substate region samples of at least 400 respondents. For substate areas that do not conform to the substate region boundaries (e.g., counties and large municipalities), HB estimates could be derived from their elemental block group level contributions, but the design-based data employed in the estimation of the associated substate region effects would not be restricted to the county or city of interest. This mismatch of FI region and county/large municipality boundaries weakens the theoretical appeal of the associated HB estimate. For this reason, substate HB estimates probably should be restricted to areas that can be matched reasonably well to FI region groups.

One of the difficulties of typical SAE has been obtaining good estimates of the accuracy of the estimates with PIs that give a good representation of the true probability of coverage of the intervals. Therefore, the final major goal was to provide accurate PIs—ones that would approach the usual sample-based intervals as the sample size increases.

B.6.3 Variables Modeled

A set of 18 measures covering a variety of aspects of substance use and abuse was designated for estimation from the 2000 NHSDA. The first 12 were based on the pooled 1999 and 2000 NHSDA data and the remaining 6 on 2000 data alone. Recall that the SAE measures of annual change evaluated in Section B.2 were not precise enough to declare significant the size of annual changes that were observed. After conferring with the SAE expert panel, the decision was made to produce averaged 1999 and 2000 State estimates for the 12 measures that were comparably defined. The 18 outcome variables are listed below:

past month use of any illicit drug, past month use of marijuana, perceptions of great risk of smoking marijuana once a month, average annual rates of first use of marijuana, past month use of any illicit drug other than marijuana, past year use of cocaine, past month use of alcohol, past month "binge" alcohol use, perceptions of great risk of having five or more drinks of an alcoholic beverage once or twice a week,

past month use of any tobacco product, past month use of cigarettes, perceptions of great risk of smoking one or more packs of cigarettes per day, past year alcohol dependence or abuse, past year alcohol dependence, past year any illicit drug dependence or abuse, past year any illicit drug dependence, past year dependence or abuse for any illicit drug or alcohol, and past year treatment gap.

Note that the "past year treatment gap" variable is not covered in this report (see, instead, OAS, 2002).

B.6.4 Predictors Used in Logistic Regression Models

Local area data used as potential predictor variables in the logistic regression models were obtained from several sources, including Claritas, the Census Bureau, the FBI (Uniform Crime Reports), Health Resources and Services Administration (Area Resource File), SAMHSA (Uniform Facility Data Set), and the National Center for Health Statistics (mortality data). The list of sources and potential data items used in the modeling are provided below.

• Claritas. The demographic data package called Building Block Basic, Age by Race for 1999 with projections to 2004 was used.
• Census Bureau. Both 1990 Census (demographic and socioeconomic variables) and July 1997 Food Stamp participation rates were used.
• Federal Bureau of Investigation. Uniform Crime Report (UCR) arrest totals were used from http://fisher.lib.Virginia.EDU/crime/; the most current data are for 1998 for most counties, and previous years' data were used in a few cases.
• Health Resources and Services Administration. Some variables were used relating to income and employment from the Area Resource File (ARF) February 2000 release from the Bureau of Health Professions, Office of Research and Planning.
• National Center for Health Statistics. Mortality data using International Classification of Diseases, 9^th revision (ICD-9), 1993 to 1998 were used. The ICD-9 death rate data are from the National Center for Health Statistics at the Centers for Disease Control and Prevention.
• SAMHSA, Office of Applied Studies. Uniform Facility Data Set (UFDS), 1997 to 1998 data on drug and alcohol treatment rates were used from Synectics for Management Decisions, Inc.

The following lists provide the specific independent variables that were potential predictors in the models.

Claritas Data
Description	Level
% Population aged 0–18 in block group	Block group
% Population aged 19–24 in block group	Block group
% Population aged 25–34 in block group	Block group
% Population aged 35–44 in block group	Block group
% Population aged 45–54 in block group	Block group
% Population aged 55–64 in block group	Block group
% Population aged 65+ in block group	Block group
% Blacks in block group	Block group
% Hispanics in block group	Block group
% Other race in block group	Block group
% Whites in block group	Block group
% Males in block group	Block group
% Females in block group	Block group
% American Indian, Eskimo, Aleut in tract	Tract
% Asian, Pacific Islander in tract	Tract
% Population aged 0–18 in tract	Tract
% Population aged 19–24 in tract	Tract
% Population aged 25–34 in tract	Tract
% Population aged 35–44 in tract	Tract
% Population aged 45–54 in tract	Tract
% Population aged 55–64 in tract	Tract
% Population aged 65+ in tract	Tract
% Blacks in tract	Tract
% Hispanics in tract	Tract
% Other race in tract	Tract
% Whites in tract	Tract
% Males in tract	Tract
% Females in tract	Tract
% Population aged 0–18 in county	County
% Population aged 19–24 in county	County
% Population aged 25–34 in county	County
% Population aged 35–44 in county	County
% Population aged 45–54 in county	County
% Population aged 55–64 in county	County
% Population aged 65+ in county	County
% Blacks in county	County
% Hispanics in county	County
% Other race in county	County
% Whites in county	County
% Males in county	County
% Females in county	County

 

1990 Census Data
Description	Level
% Population who dropped out of high school	Tract
% Housing units built in 1940–1949	Tract
% Persons 16–64 with a work disability	Tract
% Hispanics who are Cuban	Tract
% Females 16 years or older in labor force	Tract
% Females never married	Tract
% Females separated/divorced/widowed/other	Tract
% One–person households	Tract
% Female head of household, no spouse, child 18	Tract
% Males 16 years or older in labor force	Tract
% Males never married	Tract
% Males separated/divorced/widowed/other	Tract
% Housing units built in 1939 or earlier	Tract
Average persons per room	Tract
% Families below poverty level	Tract
% Households with public assistance income	Tract
% Housing units rented	Tract
% Population 9–12 years of school, no high school diploma	Tract
% Population 0–8 years of school	Tract
% Population with associate's degree	Tract
% Population some college and no degree	Tract
% Population with bachelor's, graduate, professional degree	Tract
Median rents for rental units	Tract
Median value of owner–occupied housing units	Tract
Median household income	Tract

 

Uniform Crime Report Data
Description	Level
Drug possession arrest rate	County
Drug sale/manufacture arrest rate	County
Drug violations' arrest rate	County
Marijuana possession arrest rate	County
Marijuana sale/manufacture arrest rate	County
Opium cocaine possession arrest rate	County
Opium cocaine sale/manufacture arrest rate	County
Other drug possession arrest rate	County
Other dangerous non-narcotics arrest rate	County
Serious crime arrest rate	County
Violent crime arrest rate	County

 

Categorical Data
Description	Source	Level
=1 if Hispanic, =0 otherwise	Sample	Person
=1 if non-Hispanic Black, =0 otherwise	Sample	Person
=1 if non-Hispanic Other, =0 otherwise	Sample	Person
=1 if male, =0 if female	Sample	Person
=1 if Northeast region, =0 otherwise	1990 Census	State
=1 if Midwest region, =0 otherwise	1990 Census	State
=1 if South region, =0 otherwise	1990 Census	State
=1 if MSA with 1 million +, =0 otherwise	1990 Census	County
=1 if MSA with <1 million, =0 otherwise	1990 Census	County
=1 if non-MSA urban, =0 otherwise	1990 Census	Tract
=1 if underclass tract	Urban Institute	Tract
=1 if no Cubans in tract, =0 otherwise	1990 Census	Tract
=1 if urban area, =0 if rural area	1990 Census	Tract
=1 if no arrests for dangerous non-narcotics, =0 otherwise	UCR	County

 

Miscellaneous Data
Variable Description	Source	Level
Alcohol death rate, direct cause	ICD-9	County
Alcohol death rate, indirect cause	ICD-9	County
Cigarettes death rate, direct cause	ICD-9	County
Cigarettes death rate, indirect cause	ICD-9	County
Drug death rate, direct cause	ICD-9	County
Drug death rate, indirect cause	ICD-9	County
Alcohol treatment rate	UFDS	County
Alcohol and drug treatment rate	UFDS	County
Drug treatment rate	UFDS	County
% Families below poverty level	ARF	County
Unemployment rate	ARF	County
Per capita income (in thousands)	ARF	County
Food stamp participation rate	Census Bureau	County

B.6.5 Selection of Independent Variables for the Models

For outcomes modeled using 2000 data alone, independent variables for modeling each of the substance use measures were first identified by a CHAID (Chi-squared Automatic Interaction Detector) algorithm, which does not use sample weights. Prior to this process, all the continuous variables were categorized using deciles and were treated as ordinal in CHAID. Region was treated as nominal categorical variables in CHAID. Significant (at 3 percent level) independent variables from each model and final nodes in the tree-growing process were identified as predictor variables destined for inclusion at a later step.

Independently, a SAS stepwise logistic regression model was fit for each dependent variable by age group. The SAS stepwise was used because it was able to quickly run all of the variables for all of the models, although it was recognized that the software would not take into account the complex sample design. The independent variables included all the first-order or linear polynomial trend contrasts across the 10 levels of the categorized variables plus the gender, region, and race variables. Significant variables (at the 3 percent level) were identified from this process. Based on the combined list from CHAID and SAS, a list of variables was created that included the corresponding second- and third-order polynomials and the interaction of the first-order polynomials with the gender, race, and region variables.

Next, the variables were entered into a SAS stepwise logistic model at the 1 percent significance level. Because of past concerns about overfitting of the data in earlier estimation using the 1991 to 1993 NHSDA data, the significance levels were made quite stringent. These variables were then entered into a SUDAAN logistic regression model because the SUDAAN software would adjust for the effects of the weights and other aspects of the complex sample design. All variables that were still significant at the 1 percent significance level were entered into the survey-weighted HB process.

For outcome variables modeled using pooled 1999 and 2000 data, the starting predictor set was the final predictor set used in the 1999 analyses. This set was further reduced by modeling the combined data using SUDAAN selection at the 1 percent level of significance.

B.6.6 General Model Description

The model can be characterized as a complex mixed model (including both fixed and random effects) of the form:

.

Each of the symbols represents a matrix or vector. The leading term is the usual (fixed) regression contribution, and represents random effects for the States and FI region groups that the data will support and for which estimates are desired. Not obvious from the notation is that the form of the model is a logistic model used to estimate dichotomous data. The vector has elements , where the is the propensity for the k^th person in the j^th FI composite region in the i^th State to engage in the behavior of interest (e.g., to use marijuana in the past month). Also not obvious from the notation is that the model fitting utilizes the final "sample" weights as discussed above. The "sample" weights have been adjusted for nonresponse and poststratified to known Census counts.

The estimate for each State behaves like a "weighted" average of the design-based estimate in that State and the predicted value based on the national regression model. The "weights" in this case are functions of the relative precision of the sample-based estimate for the State and the predicted estimate based on the national model. The eight large States have large samples, and thus more "weight" is given to the sample estimate relative to the model-based regression estimate. The 42 small States and the District of Columbia put relatively more "weight" on the regression estimate because of their smaller samples. The national regression estimate actually uses national parameters that are based on the pooled 1999 and 2000 sample of approximately 138,000 persons; however, the regression estimate for a specific State is based on applying the national regression parameters to that State's "local" county, block group, and tract-level predictor variables and summing to the State level. Therefore, even the national regression component of the estimate for a State includes "local" State data. For the five outcome variables presented in this report, whose State estimates were based on the 2000 data alone, the national or fixed regression coefficients were based on a sample of roughly 72,000 persons.

The goal then was to come up with the best estimates of and U. This would lead to the best estimates of , which would in turn lead to the best estimate of . Once the best estimate of for each block group and each age/race/gender cell within a block group has been estimated, the results could be weighted by the projected Census population counts at that level to make estimates for any geographic area larger than a block group.

In the model fitting for the pooled 1999 and 2000 data, the small number of predictor variables updated in 2000 were used in both their 1999 and 2000 versions when they appeared in a model. At the time the decision was made to form pooled data estimates, the schedule did not permit merging the updated versions of the predictors onto the 1999 analysis file. To produce the pooled data estimates, the updated versions of the predictors were always used (i.e., the versions on the 2000 universe file). For the block group-level population counts by age, race, and gender used to aggregate the block group-level prevalence estimates, the average of the 1999 and 2000 population counts were used in each demographic domain.

B.6.7 Implementation of Modeling

The solution to the equation for in Section B.6.6 is not straightforward but involves a series of iterative steps to generate values of the desired fixed and random effects from the underlying joint distribution. The basic process can be described as follows.

Let denote the matrix of fixed effects, be the matrix of State random effects i = 1–51, and denote the matrix of FI composite region effects j within State i. Because the goal is to estimate separate models for four age groups, it is assumed that the random effect vectors are four variate Normal with null mean vectors and 4×4 covariance matrices and , respectively. To estimate the individual effects, a Bayesian approach is used to represent the joint density function given the data by . According to the Bayes process, this can be estimated once the conditional distributions are known:

and .

To generate random draws from these distributions, Markov Chain Monte Carlo (MCMC) processes need to be used. There are a body of methods for generating pseudo-random draws from probability distributions via Markov chains. A Markov chain is fully specified by its starting distribution and the transition kernel .

Each MCMC step that involves the vector of binary outcome variables y in the conditioning set needs first to be modified by defining a pseudo-likelihood using survey weights. In defining pseudo-likelihood, weights are introduced after scaling them to the effective sample size based on a suitable design effect. Note that with the pseudo-likelihood, the covariance matrix of the pseudo-score functions is no longer equal to the pseudo-information matrix; therefore, a sandwich-type of covariance matrix was used to compute the design effect. In this process, weights are largely assumed to be noninformative (i.e., unrelated to the outcome variable y). The assumption of noninformative weights is useful in finding tractable expressions for the appropriate information matrix of the pseudo score functions. The pseudo log-likelihood remains an unbiased estimate of the finite-population log-likelihood regardless of this assumption.

Step I (this does not depend on , ).

With flat prior for , the conditional posterior is proportional to the pseudo-likelihood function. For large samples, this posterior can be approximated by the multivariate normal distribution with mean vector equal to the pseudo-maximum likelihood estimate and with asymptotic covariance matrix having the associated sandwich form. Assuming that the survey weights are noninformative makes the age group specific vectors conditionally independent of each other. Therefore, the can be updated separately at each MCMC cycle.

Step II (this does not depend on )

Here, the conditional posterior is proportional to the product of the prior .), the pseudo-likelihood function as well as the prior ; this last prior can be omitted as it does not involve . To calculate the denominator (or the normalization constant) of the posterior distribution for requires multidimensional integration and is numerically intractable. To get around this problem, the Metropolis-Hastings (M-H) algorithm is used that requires a dominating density convenient for Monte Carlo sampling. For this purpose, the mode and curvature of the conditional posterior distribution are used; these can be simply obtained from its numerator. Then a Gaussian distribution is used with matching mode and curvature to define the dominating density for M-H. As with the age group specific parameters, the State-specific random effect vectors are conditionally independent of each other and can be updated separately at each MCMC cycle.

Step III (this does not depend on )

Similar to step II.

Step IV, (here,and include all the information from y)

Here, the pseudo-likelihood involving design weights comes in implicitly through the conditioning parameters and evaluated at the current cycle. An exact conditional posterior distribution is obtained because the inverse Wishart priors for and are conjugate.

B.6.8 Remarks

• In the NHSDA application, three FI regions were combined to form a minimum of four substate regions with corresponding random effects. This was done to ensure adequate sample sizes for estimation purposes.
• There is self-calibration built in to the modeling. This is achieved via design effect-scaling of survey weights incorporated in the conditional posterior density so that small area estimates for large States become asymptotically equivalent to the design-based estimates. Similarly, survey-weighted estimates of the fixed parameters (in particular, the intercept) give calibration of the aggregate of State small area estimates to the national design-based estimate.
• For posterior variance estimation purposes, the survey weights were largely assumed to be noninformative. The survey design effects on the posterior variance are therefore restricted to unequal weighting effects. It was assumed that all the design-related clustering effects are represented by between-State and between-substate (within-State) variability of random effects. This does not take care of variability at lower levels of clustering. However, sample size is not sufficient at lower levels to support stable estimates of random effects for area segments.
• If the logistic mixed model fits well, the variance estimates should be reasonable. The self-calibration property provides some protection against model breakdown. Research is currently under way to develop a new MCMC algorithm that fully accounts for survey design effects on the small area estimate posterior PIs.

B.7 References

Folsom, R. E., & Judkins, D. R. (1997). Substance abuse in states and metropolitan areas: Model based estimates from the 1991-1993 National Household Surveys on Drug Abuse: Methodology report (DHHS Publication No. SMA 97-3140, Methodology Series M-1; September 1996 summary report available as a WordPerfect file at /methods.htm#methods). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies.

Folsom , R. E., Shah, B., & Vaish, A. (1999). Substance abuse in states: A methodological report on model based estimates from the 1994-1996 National Household Surveys on Drug Abuse. In Proceedings of the Section on Survey Research Methods of the American Statistical Association (pp. 371-375). Washington, DC: American Statistical Association.

Office of Applied Studies. (1996). Substance abuse in states and metropolitan areas: Model based estimates from the 1991-1993 National Household Surveys on Drug Abuse—Summary report (WordPerfect 6.1 file available at /analytic.htm). Rockville, MD: Substance Abuse and Mental Health Services Administration.

Office of Applied Studies. (2000). Summary of findings from the 1999 National Household Survey on Drug Abuse (DHHS Publication No. SMA 00-3466, NHSDA Series H-12; available at /p0000016.htm#special). Rockville, MD: Substance Abuse and Mental Health Services Administration.

Office of Applied Studies. (2002). National and state estimates of the drug abuse treatment gap: 2000 National Household Survey on Drug Abuse (NHSDA Series H-14, DHHS Publication No. SMA 02-3640, /nsduh.htm). Rockville, MD: Substance Abuse and Mental Health Services Administration.

RTI. (2001). SUDAAN user's manual: Release 8.0. Research Triangle Park, NC: RTI.

Table B.1 Level Estimates (P1) for 2000

State	Age in Years			Total
	12-17	18-25	26+
Past Month Use of Marijuana
CA_TX (design-based)	6.93	11.98	3.19	4.85
CA_TX (average over substates)	7.02	11.49	3.60	5.10
NY_FL (design-based)	6.95	14.61	2.33	4.20
NY_FL (average over substates)	6.84	13.97	2.76	4.46
OH_MI (design-based)	6.95	15.96	3.09	5.17
OH_MI (average over substates)	7.52	15.46	2.83	4.96
PA_IL (design-based)	6.69	14.38	2.90	4.71
PA_IL (average over substates)	6.92	14.23	2.83	4.67
Past Year Use of Cocaine
CA_TX (design-based)	2.12	4.57	0.99	1.62
CA_TX (average over substates)	2.39	4.53	1.19	1.79
NY_FL (design-based)	1.20	4.16	1.06	1.44
NY_FL (average over substates)	1.45	4.14	1.11	1.50
OH_MI (design-based)	0.96	4.20	0.78	1.24
OH_MI (average over substates)	1.30	4.12	0.83	1.31
PA_IL (design-based)	0.97	4.14	1.16	1.51
PA_IL (average over substates)	1.22	4.10	1.18	1.55
Past Month "Binge" Alcohol Use
CA_TX (design-based)	9.64	32.54	19.60	20.29
CA_TX (average over substates)	9.79	32.10	19.39	20.09
NY_FL (design-based)	9.89	37.53	17.60	19.17
NY_FL (average over substates)	10.07	36.75	18.15	19.53
OH_MI (design-based)	11.31	43.60	18.89	21.33
OH_MI (average over substates)	11.15	43.13	19.74	21.90
PA_IL (design-based)	10.35	43.41	21.81	23.37
PA_IL (average over substates)	11.00	42.93	20.88	22.66
Past Month Use of Cigarettes
CA_TX (design-based)	10.08	29.83	23.59	22.94
CA_TX (average over substates)	10.41	30.51	23.44	22.96
NY_FL (design-based)	11.67	34.94	23.38	23.59
NY_FL (average over substates)	12.36	35.14	23.12	23.48
OH_MI (design-based)	14.74	43.48	25.48	26.71
OH_MI (average over substates)	15.14	44.19	25.85	27.13
PA_IL (design-based)	13.93	44.47	24.68	26.08
PA_IL (average over substates)	14.30	43.68	24.45	25.84

Note: The average over substates is calculated as the average of the individual 2000 SAEs (P1) over the 8 substates.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

 

Table B.2 Relative Absolute Bias of Three Types of Level Estimates for 2000: Past Month Use of Marijuana

State	P1				P2				P3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
CA_TX (design-based)	6.93	11.98	3.19	4.85	6.93	11.98	3.19	4.85	6.93	11.98	3.19	4.85
CA_TX1	9.63	11.08	4.12	5.72	10.00	11.11	4.14	5.78	9.87	10.95	4.12	5.73
CA_TX2	6.16	12.17	3.67	5.15	5.96	12.30	3.51	5.03	5.86	12.00	3.26	4.79
CA_TX3	7.02	10.17	3.21	4.62	7.13	10.20	3.21	4.64	7.19	10.16	3.17	4.61
CA_TX4	6.21	9.50	3.15	4.39	6.43	9.65	3.42	4.64	6.51	9.96	3.57	4.80
CA_TX5	6.50	14.11	3.66	5.45	6.66	14.65	3.76	5.62	6.68	14.72	3.80	5.66
CA_TX6	6.93	11.88	4.00	5.44	6.82	11.72	3.81	5.27	6.71	11.39	3.49	4.99
CA_TX7	7.25	12.64	3.47	5.19	7.00	12.57	3.23	4.97	6.89	12.02	3.10	4.78
CA_TX8	6.49	10.35	3.53	4.82	6.52	10.33	3.61	4.88	6.62	10.46	3.75	5.01
Average over substates	7.02	11.49	3.60	5.10	7.07	11.57	3.59	5.10	7.04	11.46	3.53	5.05
Relative Absolute Bias	1.28	4.13	12.96	5.13	1.89	3.47	12.57	5.26	1.57	4.37	10.84	4.07
NY_FL (design-based)	6.95	14.61	2.33	4.20	6.95	14.61	2.33	4.20	6.95	14.61	2.33	4.20
NY_FL1	6.63	15.27	2.80	4.62	6.57	15.32	2.81	4.63	6.56	15.04	2.71	4.52
NY_FL2	7.28	15.13	2.54	4.46	7.34	15.27	2.55	4.49	7.34	15.23	2.59	4.52
NY_FL3	7.77	13.42	2.63	4.38	8.05	13.57	2.77	4.53	8.04	13.71	2.86	4.62
NY_FL4	6.78	12.33	2.83	4.32	6.81	12.18	2.94	4.38	7.00	12.54	3.09	4.57
NY_FL5	6.81	11.63	2.45	3.94	6.95	11.59	2.60	4.06	7.21	11.79	2.73	4.21
NY_FL6	6.84	15.55	3.30	5.06	6.74	15.65	3.27	5.05	6.71	15.73	3.31	5.08
NY_FL7	5.08	12.70	2.32	3.79	4.92	13.00	2.47	3.93	5.15	13.52	2.66	4.17
NY_FL8	7.56	15.72	3.23	5.10	7.47	15.62	3.16	5.02	7.42	15.22	3.07	4.90
Average over substates	6.84	13.97	2.76	4.46	6.86	14.03	2.82	4.51	6.93	14.10	2.88	4.57
Relative Absolute Bias	1.49	4.39	18.68	6.13	1.30	4.00	21.16	7.41	0.24	3.51	23.51	8.81
OH_MI (design-based)	6.95	15.96	3.09	5.17	6.95	15.96	3.09	5.17	6.95	15.96	3.09	5.17
OH_MI1	6.73	14.45	2.81	4.73	6.59	14.47	2.79	4.71	6.59	14.41	2.74	4.67
OH_MI2	7.13	14.56	2.67	4.68	7.07	14.50	2.62	4.63	7.11	14.66	2.69	4.71
OH_MI3	8.10	15.38	2.69	4.90	7.91	15.23	2.58	4.78	7.72	14.87	2.59	4.73
OH_MI4	8.04	16.97	3.43	5.67	7.56	16.40	3.07	5.27	7.18	15.60	2.76	4.89
OH_MI5	7.49	15.35	2.95	5.03	7.37	15.26	2.85	4.94	7.25	15.13	2.82	4.89
OH_MI6	7.01	18.04	3.21	5.54	6.60	17.98	2.98	5.31	6.40	17.64	2.83	5.13
OH_MI7	7.24	13.27	2.52	4.41	7.12	13.09	2.53	4.38	7.14	13.00	2.53	4.37
OH_MI8	8.41	15.63	2.39	4.74	8.49	15.81	2.43	4.80	8.42	15.43	2.47	4.78
Average over substates	7.52	15.46	2.83	4.96	7.34	15.34	2.73	4.85	7.22	15.09	2.68	4.77
Relative Absolute Bias	8.24	3.14	8.36	3.95	5.64	3.86	11.61	6.09	3.99	5.43	13.33	7.72
PA_IL (design-based)	6.69	14.38	2.90	4.71	6.69	14.38	2.90	4.71	6.69	14.38	2.90	4.71
PA_IL1	7.39	15.74	2.90	4.96	7.19	15.37	2.72	4.75	7.05	14.98	2.57	4.57
PA_IL2	8.50	15.02	3.61	5.53	8.68	14.85	3.62	5.53	8.50	14.69	3.57	5.46
PA_IL3	7.88	15.44	3.08	5.11	7.98	15.45	3.08	5.12	7.84	15.25	2.99	5.01
PA_IL4	5.92	12.18	2.47	4.03	5.79	12.00	2.48	4.00	5.73	11.90	2.33	3.88
PA_IL5	7.14	14.80	3.60	5.36	6.99	14.36	3.40	5.13	6.86	14.02	3.07	4.85
PA_IL6	6.95	15.16	2.32	4.39	6.88	15.46	2.37	4.46	6.87	15.68	2.39	4.50
PA_IL7	6.09	13.06	2.06	3.84	6.28	13.86	2.31	4.15	6.55	14.32	2.47	4.36
PA_IL8	5.45	12.42	2.59	4.10	5.37	12.46	2.77	4.25	5.44	12.69	2.75	4.27
Average over substates	6.92	14.23	2.83	4.67	6.89	14.23	2.84	4.67	6.85	14.19	2.77	4.61
Relative Absolute Bias	3.44	1.02	2.32	1.01	3.11	1.05	1.85	0.84	2.49	1.29	4.42	2.13
Overall	3.61	3.17	10.58	4.05	2.99	3.10	11.80	4.90	2.07	3.65	13.03	5.68

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.3 Relative Absolute Bias of Three Types of Level Estimates for 2000: Past Year Use of Cocaine

State	P1				P2				P3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
CA_TX (design-based)	2.12	4.57	0.99	1.62	2.12	4.57	0.99	1.62	2.12	4.57	0.99	1.62
CA_TX1	2.23	4.65	1.06	1.70	2.21	4.77	1.14	1.77	2.24	4.73	1.17	1.79
CA_TX2	2.83	3.76	1.31	1.83	2.83	3.65	1.27	1.78	2.89	3.62	1.20	1.73
CA_TX3	2.29	4.63	1.10	1.73	2.25	4.58	1.10	1.72	2.28	4.53	1.05	1.68
CA_TX4	2.26	3.72	1.08	1.59	2.25	3.68	1.20	1.67	2.24	3.75	1.24	1.71
CA_TX5	2.42	5.66	1.18	1.95	2.41	5.66	1.19	1.95	2.37	5.69	1.22	1.98
CA_TX6	2.18	4.70	1.00	1.66	2.17	4.82	1.06	1.71	2.13	4.76	1.08	1.71
CA_TX7	2.66	5.24	1.22	1.95	2.70	5.30	1.19	1.94	2.68	5.27	1.23	1.97
CA_TX8	2.25	3.89	1.52	1.93	2.20	3.85	1.50	1.91	2.20	3.90	1.48	1.90
Average over substates	2.39	4.53	1.19	1.79	2.38	4.54	1.21	1.81	2.38	4.53	1.21	1.81
Relative Absolute Bias	12.64	0.74	19.61	10.51	12.14	0.59	21.75	11.48	12.15	0.84	22.06	11.60
NY_FL (design-based)	1.20	4.16	1.06	1.44	1.20	4.16	1.06	1.44	1.20	4.16	1.06	1.44
NY_FL1	1.41	4.18	1.12	1.50	1.37	4.17	1.13	1.51	1.38	4.14	1.11	1.48
NY_FL2	1.44	3.63	0.95	1.31	1.45	3.67	0.98	1.34	1.47	3.69	0.99	1.35
NY_FL3	1.33	3.98	0.99	1.37	1.29	4.09	1.03	1.41	1.28	4.08	1.06	1.44
NY_FL4	1.26	3.28	0.97	1.27	1.23	3.30	1.05	1.33	1.25	3.31	1.06	1.34
NY_FL5	1.43	4.10	1.01	1.41	1.43	4.15	1.05	1.44	1.44	4.13	1.06	1.46
NY_FL6	1.94	5.79	1.46	2.01	1.90	5.64	1.34	1.89	1.91	5.45	1.27	1.81
NY_FL7	1.19	3.30	0.75	1.09	1.14	3.38	0.85	1.17	1.10	3.47	0.84	1.17
NY_FL8	1.63	4.88	1.63	2.01	1.57	4.79	1.48	1.87	1.57	4.74	1.45	1.84
Average over substates	1.45	4.14	1.11	1.50	1.42	4.15	1.11	1.50	1.42	4.13	1.10	1.48
Relative Absolute Bias	20.87	0.32	4.47	4.19	18.23	0.19	4.82	4.22	18.42	0.72	3.75	3.36
OH_MI (design-based)	0.96	4.20	0.78	1.24	0.96	4.20	0.78	1.24	0.96	4.20	0.78	1.24
OH_MI1	1.17	4.59	0.77	1.31	1.17	4.67	0.81	1.35	1.15	4.73	0.87	1.41
OH_MI2	1.07	3.21	0.70	1.06	1.05	3.30	0.79	1.14	1.09	3.29	0.83	1.17
OH_MI3	1.60	3.99	0.85	1.34	1.63	3.92	0.82	1.31	1.66	4.01	0.83	1.33
OH_MI4	1.23	4.94	0.80	1.39	1.19	5.10	0.78	1.39	1.17	5.03	0.76	1.36
OH_MI5	1.38	4.11	0.91	1.37	1.40	4.11	0.90	1.37	1.43	4.10	0.97	1.43
OH_MI6	1.10	4.58	0.72	1.26	1.05	4.68	0.74	1.29	1.04	4.63	0.77	1.30
OH_MI7	1.44	4.17	1.15	1.57	1.36	4.05	1.04	1.47	1.35	4.05	0.98	1.42
OH_MI8	1.39	3.40	0.76	1.17	1.41	3.39	0.79	1.19	1.44	3.38	0.78	1.19
Average over substates	1.30	4.12	0.83	1.31	1.28	4.15	0.83	1.31	1.29	4.15	0.85	1.33
Relative Absolute Bias	35.79	1.78	7.23	5.54	34.19	1.08	7.33	5.77	34.93	1.13	9.24	6.77
PA_IL (design-based)	0.97	4.14	1.16	1.51	0.97	4.14	1.16	1.51	0.97	4.14	1.16	1.51
PA_IL1	1.15	5.16	1.17	1.67	1.09	5.22	1.17	1.67	1.08	5.17	1.18	1.67
PA_IL2	1.09	3.98	1.40	1.69	1.01	3.75	1.38	1.64	1.00	3.83	1.31	1.61
PA_IL3	1.51	4.39	1.36	1.76	1.54	4.43	1.32	1.73	1.50	4.36	1.30	1.71
PA_IL4	1.01	3.55	0.90	1.25	0.97	3.60	1.02	1.34	0.95	3.65	1.02	1.34
PA_IL5	1.08	3.61	1.07	1.39	1.04	3.50	1.13	1.42	1.04	3.52	1.12	1.42
PA_IL6	1.27	4.87	1.15	1.63	1.29	5.04	1.17	1.66	1.27	4.95	1.17	1.65
PA_IL7	1.31	3.76	0.92	1.32	1.39	3.87	0.99	1.39	1.39	3.90	1.06	1.45
PA_IL8	1.33	3.51	1.48	1.72	1.30	3.41	1.47	1.70	1.31	3.44	1.44	1.68
Average over substates	1.22	4.10	1.18	1.55	1.20	4.10	1.21	1.57	1.19	4.10	1.20	1.57
Relative Absolute Bias	25.35	0.83	2.27	2.69	23.90	0.84	4.23	3.76	22.93	0.79	3.95	3.61
Overall	23.66	0.92	8.40	5.73	22.12	0.67	9.54	6.31	22.11	0.87	9.75	6.34

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.4 Relative Absolute Bias of Three Types of Level Estimates for 2000: Past Month "Binge" Alcohol Use

State	P1				P2				P3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
CA_TX (design-based)	9.64	32.54	19.60	20.29	9.64	32.54	19.60	20.29	9.64	32.54	19.60	20.29
CA_TX1	11.21	31.64	19.38	20.18	11.42	31.68	19.36	20.20	11.56	31.88	19.54	20.37
CA_TX2	9.54	28.90	19.71	19.85	9.75	29.02	20.41	20.42	9.77	29.06	20.97	20.81
CA_TX3	9.29	30.16	17.42	18.29	9.39	29.87	17.25	18.13	9.42	29.69	17.13	18.03
CA_TX4	8.97	33.49	19.79	20.50	8.82	34.02	20.37	20.99	8.89	34.47	20.54	21.18
CA_TX5	9.28	32.71	19.01	19.84	9.37	33.42	19.43	20.26	9.62	33.69	20.10	20.81
CA_TX6	9.71	32.28	18.07	19.13	9.81	32.79	18.17	19.28	9.78	33.16	18.22	19.37
CA_TX7	9.77	33.15	21.59	21.88	9.51	33.01	21.64	21.87	9.53	33.03	21.49	21.76
CA_TX8	10.54	34.44	20.16	21.08	10.31	33.73	19.44	20.42	10.24	32.82	18.79	19.79
Average over substates	9.79	32.10	19.39	20.09	9.80	32.19	19.51	20.20	9.85	32.22	19.60	20.26
Relative Absolute Bias	1.56	1.35	1.06	0.98	1.63	1.06	0.45	0.47	2.20	0.96	0.00	0.13
NY_FL (design-based)	9.89	37.53	17.60	19.17	9.89	37.53	17.60	19.17	9.89	37.53	17.60	19.17
NY_FL1	9.94	37.78	17.57	19.18	9.90	38.19	17.51	19.18	10.17	38.50	17.48	19.20
NY_FL2	9.99	37.17	19.81	20.88	9.80	36.91	19.99	20.98	9.71	36.94	19.84	20.85
NY_FL3	10.41	37.40	17.90	19.45	10.49	37.39	17.93	19.48	10.62	37.66	18.01	19.57
NY_FL4	9.86	38.10	18.02	19.56	9.69	38.07	17.87	19.43	9.62	37.76	17.40	19.00
NY_FL5	11.77	36.70	18.80	20.20	12.24	36.80	18.99	20.41	12.64	37.30	19.40	20.82
NY_FL6	9.55	36.69	17.27	18.78	9.51	36.82	17.26	18.79	9.79	36.92	17.47	18.99
NY_FL7	7.92	34.76	15.48	16.99	7.94	35.57	15.56	17.15	8.45	35.68	15.80	17.40
NY_FL8	11.14	35.45	20.33	21.20	11.41	34.84	20.59	21.36	11.50	35.04	20.92	21.64
Average over substates	10.07	36.75	18.15	19.53	10.12	36.82	18.22	19.60	10.31	36.97	18.29	19.69
Relative Absolute Bias	1.84	2.06	3.11	1.87	2.36	1.88	3.49	2.21	4.25	1.47	3.91	2.68
OH_MI (design-based)	11.31	43.60	18.89	21.33	11.31	43.60	18.89	21.33	11.31	43.60	18.89	21.33
OH_MI1	9.90	42.49	16.77	19.41	9.94	42.72	16.48	19.23	10.14	42.42	16.42	19.16
OH_MI2	10.80	40.97	18.80	20.86	10.80	40.57	18.47	20.56	10.66	40.41	18.39	20.46
OH_MI3	11.14	41.19	19.55	21.50	11.36	41.32	19.57	21.56	11.60	41.35	20.04	21.94
OH_MI4	11.74	43.98	21.12	23.13	11.74	43.61	20.86	22.88	11.44	43.46	20.51	22.56
OH_MI5	11.77	44.37	19.21	21.72	11.63	44.24	18.56	21.19	11.47	43.25	18.06	20.65
OH_MI6	9.84	44.45	19.44	21.70	9.56	44.66	19.26	21.56	9.41	44.26	19.14	21.41
OH_MI7	11.59	43.67	21.65	23.48	11.53	43.38	21.46	23.29	11.24	43.19	21.04	22.90
OH_MI8	12.39	43.95	21.38	23.39	12.43	43.62	21.12	23.15	12.12	43.71	20.84	22.91
Average over substates	11.15	43.13	19.74	21.90	11.12	43.02	19.47	21.68	11.01	42.76	19.30	21.50
Relative Absolute Bias	1.41	1.07	4.48	2.68	1.63	1.34	3.07	1.64	2.62	1.94	2.18	0.80
PA_IL (design-based)	10.35	43.41	21.81	23.37	10.35	43.41	21.81	23.37	10.35	43.41	21.81	23.37
PA_IL1	10.47	43.48	20.59	22.45	10.13	43.74	20.76	22.58	10.23	43.71	20.87	22.67
PA_IL2	10.73	42.29	21.37	22.93	10.59	42.26	21.55	23.05	10.48	42.23	21.67	23.13
PA_IL3	12.59	44.10	23.07	24.66	12.36	43.38	22.89	24.41	11.90	43.18	22.45	23.99
PA_IL4	9.61	42.33	20.13	21.86	9.27	42.37	20.13	21.83	9.37	42.05	19.75	21.50
PA_IL5	11.52	44.27	20.80	22.81	11.35	44.06	20.71	22.70	11.26	43.75	20.76	22.69
PA_IL6	12.20	47.99	21.00	23.50	12.03	48.47	20.78	23.37	12.40	48.07	20.88	23.44
PA_IL7	10.27	40.46	18.79	20.65	10.37	40.84	19.17	21.01	10.50	41.38	19.62	21.44
PA_IL8	10.59	38.50	21.30	22.39	10.47	37.79	21.58	22.50	10.28	37.76	21.25	22.23
Average over substates	11.00	42.93	20.88	22.66	10.82	42.86	20.95	22.68	10.80	42.77	20.91	22.64
Relative Absolute Bias	6.30	1.12	4.24	3.05	4.60	1.26	3.95	2.94	4.42	1.49	4.13	3.13
Overall	2.78	1.40	3.22	2.14	2.56	1.38	2.74	1.82	3.37	1.46	2.56	1.69

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.5 Relative Absolute Bias of Three Types of Level Estimates for 2000: Past Month Use of Cigarettes

State	P1				P2				P3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
CA_TX (design-based)	10.08	29.83	23.59	22.94	10.08	29.83	23.59	22.94	10.08	29.83	23.59	22.94
CA_TX1	11.78	30.28	23.44	23.08	11.95	29.86	23.34	22.97	12.04	29.52	23.31	22.90
CA_TX2	10.51	26.51	22.34	21.59	10.84	26.15	22.50	21.69	10.98	26.18	22.57	21.76
CA_TX3	10.53	32.31	22.40	22.45	10.42	32.47	21.98	22.15	10.38	32.66	21.79	22.03
CA_TX4	10.32	30.64	22.48	22.25	10.36	30.67	22.40	22.20	10.34	30.61	22.34	22.15
CA_TX5	10.60	31.40	24.99	24.27	10.58	31.46	25.27	24.48	10.58	31.65	25.35	24.56
CA_TX6	9.13	27.76	22.55	21.77	9.07	28.13	22.44	21.73	9.07	28.53	22.47	21.81
CA_TX7	10.63	34.24	24.94	24.63	10.40	34.52	25.08	24.75	10.50	34.21	24.89	24.57
CA_TX8	9.79	30.91	24.41	23.67	9.53	30.80	24.56	23.73	9.49	30.71	24.37	23.58
Average over substates	10.41	30.51	23.44	22.96	10.39	30.51	23.45	22.96	10.42	30.51	23.39	22.92
Relative Absolute Bias	3.32	2.27	0.63	0.10	3.15	2.26	0.63	0.09	3.44	2.27	0.88	0.09
NY_FL (design-based)	11.67	34.94	23.38	23.59	11.67	34.94	23.38	23.59	11.67	34.94	23.38	23.59
NY_FL1	11.89	38.29	24.44	24.84	11.45	38.49	24.61	24.95	11.60	38.10	24.56	24.88
NY_FL2	11.94	32.77	21.92	22.22	11.99	32.65	22.00	22.27	11.99	33.22	22.08	22.39
NY_FL3	13.05	34.88	23.61	23.90	13.04	34.47	23.64	23.88	13.12	34.50	23.48	23.76
NY_FL4	11.19	32.95	21.91	22.16	11.12	33.23	21.75	22.05	11.40	33.87	21.49	21.93
NY_FL5	13.63	37.49	24.08	24.63	13.71	37.38	24.15	24.68	13.79	37.59	24.00	24.59
NY_FL6	13.03	35.51	24.82	24.92	12.95	35.25	25.13	25.13	13.15	34.94	24.97	24.99
NY_FL7	10.77	32.25	22.21	22.27	10.74	32.62	22.23	22.33	10.91	32.98	22.49	22.59
NY_FL8	13.41	37.00	21.97	22.89	13.35	36.90	21.62	22.59	13.64	36.92	21.39	22.43
Average over substates	12.36	35.14	23.12	23.48	12.29	35.12	23.14	23.49	12.45	35.26	23.06	23.45
Relative Absolute Bias	5.97	0.57	1.11	0.48	5.37	0.52	1.02	0.45	6.72	0.92	1.38	0.62
OH_MI (design-based)	14.74	43.48	25.48	26.71	14.74	43.48	25.48	26.71	14.74	43.48	25.48	26.71
OH_MI1	14.49	43.65	25.30	26.57	14.73	43.77	25.20	26.53	14.92	43.88	25.44	26.76
OH_MI2	16.30	42.63	26.60	27.62	16.69	41.96	26.70	27.65	16.56	42.18	26.51	27.51
OH_MI3	15.11	42.62	22.57	24.41	15.39	42.55	22.24	24.18	15.70	42.35	22.35	24.27
OH_MI4	14.95	47.16	27.41	28.70	14.97	47.37	27.56	28.84	15.04	47.28	27.69	28.94
OH_MI5	15.98	46.61	25.05	26.92	15.89	46.48	24.70	26.63	16.00	45.82	24.49	26.39
OH_MI6	12.68	46.71	27.11	28.17	12.21	47.39	27.30	28.35	12.30	47.16	27.58	28.55
OH_MI7	15.15	41.87	26.73	27.50	15.42	41.66	27.06	27.76	15.51	41.92	27.34	28.02
OH_MI8	16.42	42.27	26.00	27.13	16.77	41.77	26.06	27.15	16.89	41.98	25.90	27.06
Average over substates	15.14	44.19	25.85	27.13	15.26	44.12	25.85	27.14	15.37	44.07	25.91	27.19
Relative Absolute Bias	2.65	1.64	1.44	1.55	3.48	1.48	1.47	1.58	4.22	1.37	1.71	1.78
PA_IL (design-based)	13.93	44.47	24.68	26.08	13.93	44.47	24.68	26.08	13.93	44.47	24.68	26.08
PA_IL1	13.84	42.31	24.66	25.79	13.71	42.12	24.75	25.82	13.79	42.33	24.45	25.61
PA_IL2	14.99	40.62	24.98	25.94	15.07	40.23	25.19	26.06	15.21	40.21	25.19	26.07
PA_IL3	14.14	45.30	23.91	25.62	13.97	45.04	23.61	25.33	13.94	44.78	23.53	25.24
PA_IL4	12.83	42.19	23.17	24.52	12.55	42.26	23.08	24.44	12.28	42.81	22.97	24.36
PA_IL5	13.52	48.49	25.96	27.54	13.05	48.84	26.00	27.57	12.86	48.63	26.59	27.96
PA_IL6	15.38	44.65	24.44	26.06	15.43	44.76	24.24	25.94	15.22	44.61	24.23	25.88
PA_IL7	16.07	45.51	24.38	26.20	16.25	45.68	24.19	26.09	16.08	45.40	24.37	26.18
PA_IL8	13.65	40.35	24.06	25.06	13.77	40.25	24.11	25.10	13.76	40.52	23.93	24.98
Average over substates	14.30	43.68	24.45	25.84	14.23	43.65	24.40	25.79	14.14	43.66	24.41	25.79
Relative Absolute Bias	2.64	1.79	0.93	0.93	2.10	1.85	1.13	1.11	1.51	1.82	1.09	1.14
Overall	3.65	1.57	1.03	0.76	3.53	1.53	1.06	0.81	3.97	1.59	1.27	0.91

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

Table B.6 Relative Absolute Bias of Three Types of Level Estimates for 2000

State	P1				P2				P3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
Past Month Use of Marijuana
CA_TX	1.28	4.13	12.96	5.13	1.89	3.47	12.57	5.26	1.57	4.37	10.84	4.07
NY_FL	1.49	4.39	18.68	6.13	1.30	4.00	21.16	7.41	0.24	3.51	23.51	8.81
OH_MI	8.24	3.14	8.36	3.95	5.64	3.86	11.61	6.09	3.99	5.43	13.33	7.72
PA_IL	3.44	1.02	2.32	1.01	3.11	1.05	1.85	0.84	2.49	1.29	4.42	2.13
Average	3.61	3.17	10.58	4.05	2.99	3.10	11.80	4.90	2.07	3.65	13.03	5.68
Past Year Use of Cocaine
CA_TX	12.64	0.74	19.61	10.51	12.14	0.59	21.75	11.48	12.15	0.84	22.06	11.60
NY_FL	20.87	0.32	4.47	4.19	18.23	0.19	4.82	4.22	18.42	0.72	3.75	3.36
OH_MI	35.79	1.78	7.23	5.54	34.19	1.08	7.33	5.77	34.93	1.13	9.24	6.77
PA_IL	25.35	0.83	2.27	2.69	23.90	0.84	4.23	3.76	22.93	0.79	3.95	3.61
Average	23.66	0.92	8.40	5.73	22.12	0.67	9.54	6.31	22.11	0.87	9.75	6.34
Past Month "Binge" Alcohol Use
CA_TX	1.56	1.35	1.06	0.98	1.63	1.06	0.45	0.47	2.20	0.96	0.00	0.13
NY_FL	1.84	2.06	3.11	1.87	2.36	1.88	3.49	2.21	4.25	1.47	3.91	2.68
OH_MI	1.41	1.07	4.48	2.68	1.63	1.34	3.07	1.64	2.62	1.94	2.18	0.80
PA_IL	6.30	1.12	4.24	3.05	4.60	1.26	3.95	2.94	4.42	1.49	4.13	3.13
Average	2.78	1.40	3.22	2.14	2.56	1.38	2.74	1.82	3.37	1.46	2.56	1.69
Past Month Use of Cigarettes
CA_TX	3.32	2.27	0.63	0.10	3.15	2.26	0.63	0.09	3.44	2.27	0.88	0.09
NY_FL	5.97	0.57	1.11	0.48	5.37	0.52	1.02	0.45	6.72	0.92	1.38	0.62
OH_MI	2.65	1.64	1.44	1.55	3.48	1.48	1.47	1.58	4.22	1.37	1.71	1.78
PA_IL	2.64	1.79	0.93	0.93	2.10	1.85	1.13	1.11	1.51	1.82	1.09	1.14
Average	3.65	1.57	1.03	0.76	3.53	1.53	1.06	0.81	3.97	1.59	1.27	0.91
Overall	8.43	1.76	5.81	3.17	7.80	1.67	6.28	3.46	7.88	1.89	6.65	3.65

Note: Relative absolute bias (Pi) = 100 × abs(mean of 8 substate Pi - P) / P, i = 1,2, and 3.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.7 Average 95 Percent Lower and Upper Bounds for Level Estimates (P1) for 2000

State	Age in Years						Total
	12-17		18-25		26+
	Lower	Upper	Lower	Upper	Lower	Upper	Lower	Upper
Past Month Use of Marijuana
CA_TX (design-based)	5.96	8.06	10.32	13.87	2.50	4.06	4.24	5.54
CA_TX (avg. over substates)	5.17	9.28	8.69	14.82	2.23	5.48	3.80	6.68
NY_FL (design-based)	5.96	8.08	12.85	16.56	1.76	3.08	3.66	4.82
NY_FL (avg. over substates)	4.86	9.33	10.73	17.75	1.71	4.22	3.37	5.78
OH_MI (design-based)	6.05	7.97	14.12	17.98	2.42	3.95	4.53	5.90
OH_MI (avg. over substates)	5.44	10.09	12.07	19.36	1.78	4.26	3.85	6.29
PA_IL (design-based)	5.72	7.80	12.27	16.77	2.20	3.81	4.02	5.53
PA_IL (avg. over substates)	5.02	9.26	10.95	18.06	1.78	4.28	3.56	5.99
Past Year Use of Cocaine
CA_TX (design-based)	1.67	2.69	3.69	5.65	0.58	1.68	1.25	2.10
CA_TX (avg. over substates)	1.52	3.57	2.97	6.61	0.55	2.23	1.18	2.62
NY_FL (design-based)	0.76	1.90	3.37	5.11	0.72	1.57	1.11	1.85
NY_FL (avg. over substates)	0.83	2.38	2.64	6.16	0.53	2.05	0.94	2.26
OH_MI (design-based)	0.64	1.43	3.43	5.13	0.50	1.21	0.97	1.58
OH_MI (avg. over substates)	0.72	2.16	2.66	6.10	0.40	1.53	0.86	1.91
PA_IL (design-based)	0.68	1.39	3.21	5.31	0.75	1.78	1.15	1.99
PA_IL (avg. over substates)	0.68	2.01	2.61	6.12	0.57	2.19	0.97	2.35
Past Month "Binge" Alcohol Use
CA_TX (design-based)	8.60	10.79	30.28	34.88	17.81	21.51	18.88	21.78
CA_TX (avg. over substates)	7.70	12.22	27.72	36.72	15.84	23.35	17.21	23.23
NY_FL (design-based)	8.72	11.20	35.04	40.08	15.88	19.46	17.73	20.70
NY_FL (avg. over substates)	7.73	12.84	31.92	41.79	14.76	21.94	16.65	22.68
OH_MI (design-based)	10.02	12.73	40.64	46.61	17.13	20.79	19.86	22.87
OH_MI (avg. over substates)	8.69	14.02	38.19	48.18	16.39	23.44	19.10	24.91
PA_IL (design-based)	9.14	11.69	40.46	46.41	19.99	23.74	21.87	24.94
PA_IL (avg. over substates)	8.61	13.78	38.01	47.96	17.39	24.72	19.71	25.82
Past Month Use of Cigarettes
CA_TX (design-based)	8.96	11.31	27.34	32.45	21.26	26.09	21.14	24.85
CA_TX (avg. over substates)	8.25	12.91	26.17	35.12	19.43	27.85	19.82	26.35
NY_FL (design-based)	10.15	13.38	32.68	37.28	21.64	25.21	22.19	25.05
NY_FL (avg. over substates)	9.73	15.41	30.38	40.13	19.35	27.23	20.38	26.80
OH_MI (design-based)	13.39	16.21	40.89	46.10	23.64	27.41	25.25	28.23
OH_MI (avg. over substates)	12.17	18.50	39.17	49.29	22.00	29.99	24.01	30.42
PA_IL (design-based)	12.54	15.45	42.28	46.68	22.63	26.85	24.36	27.88
PA_IL (avg. over substates)	11.53	17.45	38.63	48.82	20.65	28.56	22.73	29.14

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

Table B.8 Ratio of Widths of 95 Percent Confidence Intervals of Level Estimates for 2000

State	W1				W2				W3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
Past Month Use of Marijuana
CA_TX	0.76	0.69	0.62	0.70	0.78	0.72	0.60	0.65	0.79	0.72	0.61	0.67
NY_FL	0.67	0.74	0.66	0.72	0.72	0.76	0.66	0.69	0.74	0.77	0.71	0.73
OH_MI	0.77	0.68	0.57	0.66	0.79	0.70	0.54	0.61	0.79	0.69	0.55	0.62
PA_IL	0.71	0.64	0.57	0.61	0.76	0.67	0.57	0.58	0.76	0.67	0.58	0.60
Average	0.72	0.69	0.60	0.67	0.76	0.71	0.59	0.63	0.77	0.72	0.61	0.65
Past Year Use of Cocaine
CA_TX	0.65	0.71	0.51	0.62	0.69	0.73	0.47	0.57	0.71	0.75	0.51	0.59
NY_FL	0.50	0.70	0.59	0.72	0.54	0.75	0.55	0.67	0.57	0.77	0.57	0.69
OH_MI	0.52	0.65	0.49	0.59	0.58	0.70	0.47	0.56	0.62	0.73	0.51	0.58
PA_IL	0.53	0.62	0.62	0.67	0.59	0.66	0.59	0.63	0.62	0.68	0.63	0.64
Average	0.55	0.67	0.55	0.65	0.60	0.71	0.52	0.61	0.63	0.73	0.55	0.62
Past Month "Binge" Alcohol Use
CA_TX	0.68	0.73	0.65	0.67	0.74	0.78	0.71	0.71	0.75	0.78	0.72	0.71
NY_FL	0.64	0.69	0.73	0.73	0.71	0.71	0.76	0.74	0.73	0.71	0.77	0.75
OH_MI	0.66	0.66	0.77	0.74	0.73	0.68	0.81	0.77	0.73	0.68	0.81	0.76
PA_IL	0.72	0.63	0.70	0.69	0.77	0.67	0.75	0.71	0.78	0.67	0.75	0.72
Average	0.68	0.68	0.71	0.71	0.74	0.71	0.76	0.73	0.75	0.71	0.76	0.74
Past Month Use of Cigarettes
CA_TX	0.69	0.74	0.61	0.61	0.75	0.79	0.67	0.66	0.76	0.79	0.68	0.67
NY_FL	0.65	0.69	0.74	0.75	0.71	0.72	0.81	0.81	0.73	0.73	0.82	0.81
OH_MI	0.77	0.77	0.72	0.71	0.84	0.80	0.80	0.77	0.86	0.81	0.81	0.78
PA_IL	0.68	0.75	0.68	0.66	0.73	0.80	0.74	0.71	0.74	0.81	0.75	0.72
Average	0.70	0.74	0.69	0.68	0.76	0.78	0.76	0.74	0.77	0.79	0.76	0.74
Overall	0.66	0.69	0.64	0.68	0.71	0.73	0.66	0.68	0.73	0.74	0.67	0.69

W1 = WP1 / WP, W2 = WP2 / WP, and W3 = WP3 / WP

where

WP1 = mean of widths of PIs of P1 over substates,
WP2 = mean of widths of PIs of P2 over substates,
WP3 = mean of widths of PIs of P3 over substates, and
WP = mean of widths of CIs of 2000 design-based estimate over substates.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.9 Relative Absolute Bias of Three Types of Change Estimates for 2000/1999: Past Month Use of Marijuana

State	R1				R2				R3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
CA_TX (design-based)	0.99	0.92	1.06	1.00	0.99	0.92	1.06	1.00	0.99	0.92	1.06	1.00
CA_TX1	1.13	0.76	1.20	1.03	1.17	0.77	1.20	1.04	1.16	0.75	1.20	1.03
CA_TX2	0.96	1.16	1.24	1.17	0.93	1.17	1.18	1.14	0.91	1.14	1.10	1.09
CA_TX3	0.97	0.86	1.07	0.98	0.99	0.87	1.08	0.99	1.00	0.86	1.06	0.98
CA_TX4	0.85	0.72	0.91	0.84	0.88	0.74	0.99	0.89	0.89	0.76	1.04	0.92
CA_TX5	0.71	0.98	1.00	0.95	0.73	1.02	1.03	0.98	0.73	1.02	1.04	0.98
CA_TX6	0.93	1.00	1.48	1.21	0.92	0.99	1.41	1.17	0.90	0.96	1.29	1.11
CA_TX7	1.39	1.13	1.15	1.18	1.34	1.12	1.07	1.13	1.32	1.07	1.03	1.08
CA_TX8	1.10	0.75	1.03	0.94	1.10	0.75	1.05	0.95	1.12	0.76	1.09	0.97
Average over substates	1.01	0.92	1.14	1.04	1.01	0.93	1.13	1.04	1.00	0.92	1.11	1.02
Relative Absolute Bias	1.27	0.47	7.01	3.72	1.50	1.07	6.27	3.58	1.16	0.03	4.23	2.18
NY_FL (design-based)	1.22	0.91	0.78	0.88	1.22	0.91	0.78	0.88	1.22	0.91	0.78	0.88
NY_FL1	0.94	1.03	1.13	1.06	0.93	1.03	1.14	1.07	0.93	1.02	1.09	1.04
NY_FL2	1.17	1.02	0.87	0.97	1.18	1.03	0.88	0.98	1.18	1.03	0.89	0.98
NY_FL3	1.10	0.84	0.85	0.88	1.14	0.85	0.90	0.91	1.14	0.85	0.93	0.93
NY_FL4	1.15	0.77	0.87	0.87	1.16	0.76	0.90	0.88	1.19	0.79	0.95	0.92
NY_FL5	1.05	0.72	0.90	0.85	1.07	0.72	0.96	0.88	1.11	0.73	1.01	0.91
NY_FL6	1.02	0.99	1.07	1.04	1.00	1.00	1.07	1.03	1.00	1.00	1.08	1.04
NY_FL7	0.88	0.90	0.75	0.82	0.86	0.92	0.80	0.85	0.90	0.96	0.86	0.90
NY_FL8	1.06	1.03	1.20	1.12	1.05	1.02	1.17	1.10	1.05	1.00	1.14	1.07
Average over substates	1.05	0.91	0.96	0.95	1.05	0.92	0.98	0.96	1.06	0.92	0.99	0.97
Relative Absolute Bias	14.24	0.19	23.35	7.73	14.11	0.25	25.80	8.99	13.10	0.76	27.95	10.34
OH_MI (design-based)	1.02	1.08	1.09	1.08	1.02	1.08	1.09	1.08	1.02	1.08	1.09	1.08
OH_MI1	0.84	0.99	1.11	1.02	0.82	0.99	1.11	1.01	0.82	0.99	1.09	1.00
OH_MI2	1.09	0.91	0.91	0.94	1.08	0.91	0.90	0.93	1.08	0.92	0.92	0.94
OH_MI3	1.27	1.00	0.95	1.01	1.24	0.99	0.91	0.99	1.21	0.97	0.91	0.98
OH_MI4	1.13	1.29	1.50	1.35	1.06	1.25	1.34	1.25	1.01	1.19	1.20	1.17
OH_MI5	0.96	1.07	1.02	1.03	0.94	1.06	0.99	1.01	0.93	1.06	0.98	1.00
OH_MI6	0.93	1.29	1.21	1.19	0.88	1.28	1.12	1.14	0.85	1.26	1.06	1.11
OH_MI7	1.03	0.94	1.02	0.99	1.01	0.92	1.02	0.98	1.02	0.92	1.02	0.98
OH_MI8	1.06	0.98	0.87	0.95	1.07	0.99	0.89	0.96	1.06	0.97	0.90	0.96
Average over substates	1.04	1.06	1.07	1.06	1.01	1.05	1.03	1.04	1.00	1.03	1.01	1.02
Relative Absolute Bias	1.24	1.83	1.11	1.43	1.22	2.61	4.78	3.74	2.78	4.26	6.87	5.52
PA_IL (design-based)	0.87	1.02	1.20	1.07	0.87	1.02	1.20	1.07	0.87	1.02	1.20	1.07
PA_IL1	1.23	1.17	1.14	1.17	1.20	1.14	1.07	1.12	1.17	1.11	1.01	1.08
PA_IL2	1.06	0.90	1.19	1.05	1.08	0.89	1.19	1.05	1.06	0.88	1.17	1.04
PA_IL3	0.97	0.94	1.17	1.04	0.98	0.94	1.17	1.05	0.96	0.93	1.13	1.02
PA_IL4	1.01	0.94	1.13	1.03	0.99	0.92	1.13	1.03	0.98	0.92	1.06	0.99
PA_IL5	0.86	1.09	1.55	1.24	0.84	1.05	1.46	1.19	0.82	1.03	1.32	1.12
PA_IL6	0.99	1.09	0.82	0.95	0.98	1.11	0.84	0.96	0.98	1.13	0.84	0.97
PA_IL7	0.78	0.81	0.72	0.77	0.80	0.86	0.80	0.83	0.84	0.89	0.86	0.87
PA_IL8	0.75	0.89	1.08	0.95	0.74	0.90	1.16	0.98	0.75	0.91	1.15	0.99
Average over substates	0.96	0.98	1.10	1.03	0.95	0.98	1.10	1.03	0.94	0.97	1.07	1.01
Relative Absolute Bias	10.45	4.08	8.70	4.45	9.91	4.22	8.43	4.43	9.22	4.49	11.13	5.80
Overall	6.80	1.64	10.04	4.33	6.69	2.04	11.32	5.18	6.57	2.39	12.55	5.96

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.10 Relative Absolute Bias of Three Types of Change Estimates for 2000/1999: Past Year Use of Cocaine

State	R1				R2				R3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
CA_TX (design-based)	0.86	0.75	0.80	0.79	0.86	0.75	0.80	0.79	0.86	0.75	0.80	0.79
CA_TX1	0.96	0.68	0.70	0.72	0.95	0.69	0.75	0.75	0.97	0.69	0.77	0.76
CA_TX2	1.14	0.66	1.03	0.90	1.14	0.64	0.99	0.88	1.16	0.63	0.94	0.85
CA_TX3	1.09	0.96	0.89	0.94	1.07	0.95	0.89	0.94	1.09	0.94	0.85	0.92
CA_TX4	0.89	0.59	0.65	0.66	0.89	0.59	0.72	0.69	0.89	0.60	0.75	0.71
CA_TX5	1.01	0.99	0.73	0.86	1.01	0.99	0.73	0.86	0.99	1.00	0.75	0.87
CA_TX6	0.91	0.70	0.72	0.74	0.91	0.72	0.76	0.76	0.89	0.71	0.77	0.76
CA_TX7	1.26	0.84	0.76	0.84	1.28	0.85	0.74	0.84	1.27	0.85	0.76	0.85
CA_TX8	0.87	0.62	1.05	0.87	0.86	0.62	1.04	0.85	0.85	0.63	1.03	0.85
Average over substates	1.02	0.76	0.81	0.82	1.01	0.76	0.83	0.82	1.01	0.75	0.83	0.82
Relative Absolute Bias	18.13	0.70	2.23	3.33	17.63	0.74	3.86	4.10	17.66	0.47	3.78	4.08
NY_FL (design-based)	0.82	0.77	0.96	0.88	0.82	0.77	0.96	0.88	0.82	0.77	0.96	0.88
NY_FL1	0.87	0.85	0.71	0.76	0.85	0.85	0.71	0.76	0.86	0.84	0.70	0.75
NY_FL2	0.89	0.75	0.59	0.66	0.90	0.76	0.61	0.68	0.91	0.76	0.61	0.68
NY_FL3	0.82	0.71	0.58	0.64	0.80	0.73	0.61	0.66	0.79	0.73	0.63	0.67
NY_FL4	0.81	0.64	0.60	0.62	0.79	0.64	0.65	0.66	0.81	0.64	0.65	0.66
NY_FL5	1.03	0.78	0.59	0.67	1.03	0.79	0.61	0.69	1.03	0.79	0.62	0.69
NY_FL6	1.25	1.14	0.90	1.00	1.23	1.11	0.83	0.94	1.23	1.07	0.78	0.90
NY_FL7	0.60	0.77	0.51	0.59	0.58	0.79	0.57	0.63	0.56	0.81	0.57	0.63
NY_FL8	1.05	0.98	0.90	0.94	1.01	0.97	0.82	0.88	1.01	0.96	0.80	0.86
Average over substates	0.92	0.83	0.67	0.74	0.90	0.83	0.68	0.74	0.90	0.83	0.67	0.73
Relative Absolute Bias	11.60	7.11	29.72	16.12	9.25	7.26	29.32	16.02	9.50	6.75	30.05	16.72
OH_MI (design-based)	1.15	0.72	0.77	0.77	1.15	0.72	0.77	0.77	1.15	0.72	0.77	0.77
OH_MI1	1.07	0.82	0.63	0.74	1.07	0.83	0.65	0.75	1.04	0.84	0.71	0.79
OH_MI2	1.14	0.51	0.60	0.59	1.12	0.53	0.67	0.63	1.15	0.52	0.71	0.65
OH_MI3	1.80	0.86	0.78	0.87	1.83	0.84	0.75	0.85	1.86	0.86	0.76	0.87
OH_MI4	1.20	1.08	0.97	1.04	1.15	1.11	0.94	1.03	1.14	1.09	0.91	1.01
OH_MI5	1.53	0.76	0.72	0.78	1.56	0.76	0.72	0.78	1.58	0.76	0.77	0.81
OH_MI6	1.15	1.00	0.71	0.86	1.10	1.02	0.73	0.88	1.09	1.01	0.76	0.89
OH_MI7	1.48	0.95	1.26	1.15	1.40	0.93	1.14	1.07	1.39	0.93	1.07	1.04
OH_MI8	1.51	0.69	0.81	0.80	1.53	0.69	0.84	0.82	1.56	0.68	0.83	0.82
Average over substates	1.36	0.83	0.81	0.85	1.34	0.84	0.81	0.85	1.35	0.84	0.81	0.86
Relative Absolute Bias	17.73	15.76	5.15	11.09	16.45	16.49	4.79	11.04	17.19	16.40	5.97	11.77
PA_IL (design-based)	0.84	0.99	1.22	1.10	0.84	0.99	1.22	1.10	0.84	0.99	1.22	1.10
PA_IL1	1.14	1.11	1.32	1.22	1.09	1.12	1.32	1.23	1.08	1.11	1.34	1.23
PA_IL2	0.90	1.17	1.60	1.38	0.83	1.10	1.58	1.34	0.83	1.12	1.51	1.32
PA_IL3	1.32	0.96	1.53	1.28	1.34	0.97	1.47	1.26	1.31	0.95	1.46	1.24
PA_IL4	0.76	0.86	1.07	0.96	0.73	0.88	1.21	1.03	0.71	0.89	1.21	1.03
PA_IL5	0.91	0.75	1.27	1.01	0.87	0.73	1.34	1.03	0.87	0.73	1.32	1.03
PA_IL6	1.12	1.05	1.27	1.17	1.14	1.09	1.29	1.20	1.12	1.07	1.29	1.19
PA_IL7	1.17	0.74	0.92	0.87	1.24	0.76	0.99	0.91	1.24	0.77	1.06	0.95
PA_IL8	1.26	0.85	1.58	1.28	1.23	0.83	1.56	1.26	1.25	0.83	1.53	1.25
Average over substates	1.07	0.94	1.32	1.15	1.06	0.93	1.35	1.16	1.05	0.93	1.34	1.15
Relative Absolute Bias	28.03	5.70	8.09	3.77	26.59	5.97	10.21	4.76	25.65	5.82	9.80	4.54
Overall	18.87	7.32	11.30	8.58	17.48	7.61	12.04	8.98	17.50	7.36	12.40	9.28

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.11 Relative Absolute Bias of Three Types of Change Estimates for 2000/1999: Past Month "Binge" Alcohol Use

State	R1				R2				R3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
CA_TX (design-based)	0.95	0.93	1.05	1.02	0.95	0.93	1.05	1.02	0.95	0.93	1.05	1.02
CA_TX1	1.10	0.90	1.00	0.98	1.12	0.90	0.99	0.98	1.14	0.91	1.00	0.99
CA_TX2	0.90	0.81	1.08	1.00	0.92	0.81	1.12	1.03	0.92	0.81	1.15	1.05
CA_TX3	1.01	0.96	1.12	1.07	1.02	0.95	1.11	1.06	1.02	0.94	1.10	1.06
CA_TX4	0.82	0.97	1.00	0.98	0.81	0.99	1.03	1.01	0.82	1.00	1.04	1.02
CA_TX5	0.77	0.85	1.00	0.95	0.77	0.87	1.02	0.97	0.79	0.88	1.06	1.00
CA_TX6	0.85	0.96	0.97	0.96	0.86	0.98	0.98	0.97	0.85	0.99	0.98	0.98
CA_TX7	1.14	1.02	1.02	1.03	1.11	1.02	1.03	1.03	1.11	1.02	1.02	1.02
CA_TX8	1.38	1.01	1.21	1.17	1.35	0.99	1.17	1.13	1.34	0.97	1.13	1.10
Average over substates	1.00	0.94	1.05	1.02	0.99	0.94	1.06	1.02	1.00	0.94	1.06	1.03
Relative Absolute Bias	4.87	0.55	0.32	0.41	4.77	0.80	0.83	0.84	5.26	0.89	1.21	1.11
NY_FL (design-based)	1.17	1.00	0.94	0.96	1.17	1.00	0.94	0.96	1.17	1.00	0.94	0.96
NY_FL1	1.20	1.05	0.87	0.92	1.19	1.06	0.86	0.92	1.23	1.07	0.86	0.92
NY_FL2	1.08	0.99	1.16	1.12	1.06	0.99	1.17	1.12	1.05	0.99	1.16	1.11
NY_FL3	1.07	1.03	0.97	0.99	1.08	1.03	0.97	0.99	1.10	1.04	0.98	1.00
NY_FL4	1.21	1.14	1.04	1.07	1.19	1.14	1.03	1.06	1.18	1.13	1.00	1.03
NY_FL5	1.22	0.91	0.91	0.93	1.27	0.92	0.92	0.93	1.31	0.93	0.94	0.95
NY_FL6	1.14	0.99	0.89	0.92	1.14	0.99	0.89	0.92	1.17	1.00	0.90	0.93
NY_FL7	0.88	0.90	0.90	0.90	0.88	0.92	0.91	0.91	0.94	0.92	0.92	0.92
NY_FL8	1.01	0.87	1.15	1.08	1.03	0.85	1.17	1.09	1.04	0.86	1.19	1.10
Average over substates	1.10	0.99	0.99	0.99	1.11	0.99	0.99	0.99	1.13	0.99	0.99	1.00
Relative Absolute Bias	6.17	1.21	5.30	3.05	5.81	1.02	5.70	3.38	4.06	0.63	6.09	3.81
OH_MI (design-based)	1.19	1.08	0.92	0.97	1.19	1.08	0.92	0.97	1.19	1.08	0.92	0.97
OH_MI1	0.93	1.04	0.85	0.90	0.94	1.04	0.84	0.90	0.96	1.04	0.84	0.89
OH_MI2	1.14	1.07	0.94	0.98	1.14	1.06	0.92	0.96	1.13	1.05	0.92	0.96
OH_MI3	1.04	0.92	0.94	0.94	1.06	0.92	0.94	0.94	1.08	0.92	0.97	0.96
OH_MI4	1.13	1.12	1.04	1.06	1.13	1.11	1.03	1.05	1.10	1.10	1.01	1.04
OH_MI5	1.38	1.13	1.01	1.06	1.37	1.13	0.98	1.03	1.35	1.10	0.95	1.01
OH_MI6	1.07	1.15	0.99	1.03	1.04	1.16	0.98	1.03	1.02	1.15	0.98	1.02
OH_MI7	1.19	1.14	1.06	1.08	1.18	1.13	1.05	1.07	1.15	1.12	1.03	1.05
OH_MI8	1.15	1.12	0.93	0.98	1.16	1.11	0.92	0.97	1.13	1.11	0.90	0.96
Average over substates	1.13	1.08	0.97	1.01	1.13	1.08	0.96	0.99	1.11	1.07	0.95	0.99
Relative Absolute Bias	5.25	0.20	5.84	3.71	5.52	0.08	4.39	2.64	6.52	0.69	3.47	1.77
PA_IL (design-based)	0.99	1.07	1.08	1.08	0.99	1.07	1.08	1.08	0.99	1.07	1.08	1.08
PA_IL1	1.07	1.06	0.99	1.01	1.04	1.06	1.00	1.02	1.05	1.06	1.01	1.02
PA_IL2	1.00	1.05	1.07	1.06	0.98	1.05	1.08	1.07	0.97	1.05	1.09	1.07
PA_IL3	1.07	1.10	1.23	1.19	1.05	1.09	1.22	1.18	1.01	1.08	1.19	1.16
PA_IL4	1.03	1.05	1.04	1.05	1.00	1.05	1.04	1.04	1.01	1.04	1.02	1.03
PA_IL5	1.06	1.05	1.06	1.06	1.05	1.04	1.06	1.06	1.04	1.03	1.06	1.06
PA_IL6	1.20	1.06	0.94	0.98	1.18	1.07	0.93	0.97	1.22	1.06	0.93	0.98
PA_IL7	0.87	0.97	0.91	0.93	0.88	0.98	0.93	0.94	0.89	1.00	0.96	0.96
PA_IL8	1.11	1.01	1.09	1.07	1.10	0.99	1.10	1.08	1.08	0.99	1.08	1.06
Average over substates	1.05	1.04	1.04	1.04	1.03	1.04	1.05	1.05	1.03	1.04	1.04	1.04
Relative Absolute Bias	6.66	2.60	3.71	3.04	4.89	2.78	3.41	2.94	4.78	3.00	3.63	3.16
Overall	5.74	1.14	3.79	2.55	5.25	1.17	3.58	2.45	5.15	1.30	3.60	2.46

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.12 Relative Absolute Bias of Three Types of Change Estimates for 2000/1999: Past Month Use of Cigarettes

State	R1				R2				R3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
CA_TX (design-based)	0.95	0.89	1.11	1.05	0.95	0.89	1.11	1.05	0.95	0.89	1.11	1.05
CA_TX1	1.05	0.85	1.08	1.03	1.07	0.84	1.08	1.02	1.08	0.83	1.07	1.02
CA_TX2	0.94	0.75	1.04	0.97	0.97	0.74	1.04	0.97	0.98	0.74	1.05	0.98
CA_TX3	0.89	1.00	1.00	1.00	0.88	1.01	0.98	0.98	0.87	1.01	0.98	0.98
CA_TX4	0.91	0.89	1.01	0.98	0.92	0.89	1.00	0.98	0.92	0.89	1.00	0.97
CA_TX5	0.84	0.92	1.13	1.07	0.84	0.92	1.15	1.08	0.84	0.93	1.15	1.08
CA_TX6	0.78	0.88	1.03	0.98	0.78	0.89	1.02	0.98	0.78	0.90	1.02	0.98
CA_TX7	1.01	0.97	1.15	1.11	0.99	0.98	1.16	1.11	1.00	0.97	1.15	1.10
CA_TX8	0.88	0.91	1.17	1.10	0.86	0.91	1.18	1.10	0.85	0.91	1.17	1.09
Average over substates	0.91	0.90	1.08	1.03	0.91	0.90	1.08	1.03	0.91	0.90	1.07	1.03
Relative Absolute Bias	4.09	0.37	2.75	2.34	4.25	0.39	2.73	2.35	3.97	0.42	2.98	2.53
NY_FL (design-based)	1.00	0.97	0.91	0.92	1.00	0.97	0.91	0.92	1.00	0.97	0.91	0.92
NY_FL1	0.88	0.99	1.01	1.00	0.85	0.99	1.01	1.00	0.86	0.98	1.01	1.00
NY_FL2	0.82	0.89	0.88	0.88	0.83	0.89	0.88	0.88	0.83	0.90	0.89	0.89
NY_FL3	0.95	0.93	0.97	0.96	0.95	0.92	0.97	0.96	0.96	0.92	0.96	0.96
NY_FL4	0.85	0.92	0.81	0.83	0.85	0.93	0.81	0.83	0.87	0.95	0.80	0.82
NY_FL5	0.92	0.98	0.90	0.92	0.93	0.97	0.91	0.92	0.93	0.98	0.90	0.92
NY_FL6	1.01	0.89	1.03	1.00	1.01	0.89	1.04	1.01	1.02	0.88	1.03	1.01
NY_FL7	0.82	0.87	0.94	0.92	0.82	0.88	0.94	0.93	0.83	0.89	0.95	0.94
NY_FL8	1.06	1.03	0.83	0.87	1.05	1.03	0.82	0.86	1.08	1.03	0.81	0.86
Average over substates	0.92	0.94	0.92	0.92	0.91	0.94	0.92	0.92	0.92	0.94	0.92	0.92
Relative Absolute Bias	8.29	2.82	1.18	0.07	8.83	2.87	1.30	0.02	7.63	2.45	0.95	0.18
OH_MI (design-based)	0.88	0.94	0.91	0.91	0.88	0.94	0.91	0.91	0.88	0.94	0.91	0.91
OH_MI1	0.77	0.93	0.85	0.86	0.78	0.93	0.85	0.86	0.79	0.94	0.85	0.87
OH_MI2	0.95	1.02	0.88	0.91	0.97	1.00	0.88	0.91	0.96	1.01	0.88	0.91
OH_MI3	0.90	0.92	0.81	0.84	0.92	0.92	0.80	0.83	0.94	0.91	0.80	0.83
OH_MI4	0.81	1.03	0.95	0.96	0.81	1.03	0.96	0.96	0.82	1.03	0.96	0.97
OH_MI5	1.05	1.04	0.93	0.96	1.04	1.04	0.92	0.95	1.05	1.02	0.91	0.94
OH_MI6	0.76	0.99	0.99	0.98	0.73	1.00	1.00	0.98	0.74	0.99	1.01	0.99
OH_MI7	0.82	0.88	0.91	0.90	0.84	0.87	0.92	0.91	0.84	0.88	0.93	0.91
OH_MI8	1.00	1.00	0.90	0.93	1.03	0.99	0.90	0.93	1.03	0.99	0.90	0.92
Average over substates	0.88	0.97	0.90	0.92	0.89	0.97	0.90	0.92	0.90	0.97	0.91	0.92
Relative Absolute Bias	0.50	3.39	0.22	0.48	1.28	3.19	0.21	0.50	2.00	3.09	0.02	0.68
PA_IL (design-based)	0.78	1.08	0.95	0.97	0.78	1.08	0.95	0.97	0.78	1.08	0.95	0.97
PA_IL1	0.90	1.06	0.91	0.93	0.89	1.05	0.91	0.94	0.90	1.06	0.90	0.93
PA_IL2	0.92	0.93	0.95	0.95	0.92	0.92	0.96	0.95	0.93	0.92	0.96	0.95
PA_IL3	0.82	1.07	0.91	0.94	0.81	1.07	0.90	0.93	0.81	1.06	0.90	0.93
PA_IL4	0.77	1.14	0.90	0.94	0.75	1.14	0.90	0.94	0.74	1.16	0.90	0.93
PA_IL5	0.68	1.06	1.06	1.03	0.65	1.07	1.06	1.03	0.64	1.06	1.08	1.05
PA_IL6	0.95	1.06	0.92	0.95	0.96	1.06	0.91	0.94	0.94	1.05	0.91	0.94
PA_IL7	0.99	1.06	0.97	0.99	1.00	1.06	0.97	0.99	0.99	1.06	0.97	0.99
PA_IL8	0.80	1.01	0.82	0.85	0.81	1.01	0.82	0.85	0.81	1.01	0.82	0.85
Average over substates	0.85	1.05	0.93	0.95	0.85	1.05	0.93	0.95	0.84	1.05	0.93	0.95
Relative Absolute Bias	9.48	2.58	2.51	2.02	8.98	2.66	2.71	2.21	8.37	2.59	2.64	2.23
Overall	5.59	2.29	1.66	1.23	5.83	2.28	1.74	1.27	5.49	2.14	1.65	1.40

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.13 Change Estimates (R1) for 2000/1999

State	Age in Years			Total
	12-17	18-25	26+
Past Month Use of Marijuana
CA_TX (design-based)	0.99	0.92	1.06	1.00
CA_TX (average over substates)	1.01	0.92	1.14	1.04
NY_FL (design-based)	1.22	0.91	0.78	0.88
NY_FL (average over substates)	1.05	0.91	0.96	0.95
OH_MI (design-based)	1.02	1.08	1.09	1.08
OH_MI (average over substates)	1.04	1.06	1.07	1.06
PA_IL (design-based)	0.87	1.02	1.20	1.07
PA_IL (average over substates)	0.96	0.98	1.10	1.03
Past Year Use of Cocaine
CA_TX (design-based)	0.86	0.75	0.80	0.79
CA_TX (average over substates)	1.02	0.76	0.81	0.82
NY_FL (design-based)	0.82	0.77	0.96	0.88
NY_FL (average over substates)	0.92	0.83	0.67	0.74
OH_MI (design-based)	1.15	0.72	0.77	0.77
OH_MI (average over substates)	1.36	0.83	0.81	0.85
PA_IL (design-based)	0.84	0.99	1.22	1.10
PA_IL (average over substates)	1.07	0.94	1.32	1.15
Past Month "Binge" Alcohol Use
CA_TX (design-based)	0.95	0.93	1.05	1.02
CA_TX (average over substates)	1.00	0.94	1.05	1.02
NY_FL (design-based)	1.17	1.00	0.94	0.96
NY_FL (average over substates)	1.10	0.99	0.99	0.99
OH_MI (design-based)	1.19	1.08	0.92	0.97
OH_MI (average over substates)	1.13	1.08	0.97	1.01
PA_IL (design-based)	0.99	1.07	1.08	1.08
PA_IL (average over substates)	1.05	1.04	1.04	1.04
Past Month Use of Cigarettes
CA_TX (design-based)	0.95	0.89	1.11	1.05
CA_TX (average over substates)	0.91	0.90	1.08	1.03
NY_FL (design-based)	1.00	0.97	0.91	0.92
NY_FL (average over substates)	0.92	0.94	0.92	0.92
OH_MI (design-based)	0.88	0.94	0.91	0.91
OH_MI (average over substates)	0.88	0.97	0.90	0.92
PA_IL (design-based)	0.78	1.08	0.95	0.97
PA_IL (average over substates)	0.85	1.05	0.93	0.95

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.14 Relative Absolute Bias of Three Types of Change Estimates for 2000/1999

State	R1				R2				R3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
Past Month Use of Marijuana
CA_TX	1.27	0.47	7.01	3.72	1.50	1.07	6.27	3.58	1.16	0.03	4.23	2.18
NY_FL	14.24	0.19	23.35	7.73	14.11	0.25	25.80	8.99	13.10	0.76	27.95	10.34
OH_MI	1.24	1.83	1.11	1.43	1.22	2.61	4.78	3.74	2.78	4.26	6.87	5.52
PA_IL	10.45	4.08	8.70	4.45	9.91	4.22	8.43	4.43	9.22	4.49	11.13	5.80
Average	6.80	1.64	10.04	4.33	6.68	2.04	11.32	5.18	6.57	2.39	12.55	5.96
Past Year Use of Cocaine
CA_TX	18.13	0.70	2.23	3.33	17.63	0.74	3.86	4.10	17.66	0.47	3.78	4.08
NY_FL	11.60	7.11	29.72	16.12	9.25	7.26	29.32	16.02	9.50	6.75	30.05	16.72
OH_MI	17.73	15.76	5.15	11.09	16.45	16.49	4.79	11.04	17.19	16.40	5.97	11.77
PA_IL	28.03	5.70	8.09	3.77	26.59	5.97	10.21	4.76	25.65	5.82	9.80	4.54
Average	18.87	7.32	11.30	8.58	17.48	7.61	12.04	8.98	17.50	7.36	12.40	9.28
Past Month "Binge" Alcohol Use
CA_TX	4.87	0.55	0.32	0.41	4.77	0.80	0.83	0.84	5.26	0.89	1.21	1.11
NY_FL	6.17	1.21	5.30	3.05	5.81	1.02	5.70	3.38	4.06	0.63	6.09	3.81
OH_MI	5.25	0.20	5.84	3.71	5.52	0.08	4.39	2.64	6.52	0.69	3.47	1.77
PA_IL	6.66	2.60	3.71	3.03	4.89	2.78	3.41	2.94	4.77	3.00	3.63	3.16
Average	5.74	1.14	3.79	2.55	5.25	1.17	3.58	2.45	5.15	1.30	3.60	2.46
Past Month Use of Cigarettes
CA_TX	4.09	0.37	2.75	2.34	4.25	0.39	2.73	2.35	3.97	0.42	2.98	2.53
NY_FL	8.29	2.82	1.18	0.07	8.83	2.87	1.30	0.02	7.63	2.45	0.95	0.18
OH_MI	0.50	3.39	0.22	0.48	1.28	3.19	0.21	0.50	2.00	3.08	0.02	0.68
PA_IL	9.48	2.58	2.51	2.02	8.98	2.66	2.71	2.21	8.37	2.59	2.64	2.23
Average	5.59	2.29	1.66	1.23	5.83	2.28	1.74	1.27	5.49	2.14	1.65	1.40
Overall	9.25	3.10	6.70	4.17	8.81	3.27	7.17	4.47	8.68	3.30	7.55	4.78

Note: Relative absolute bias (Ri) = 100 × abs(mean of 8 substate Ri - R) / R, i = 1, 2, and 3, where R = ratio of 2000 design-based estimates to 1999 design-based estimates.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.15 Average 95 Percent Lower and Upper Bounds for Change Estimates (R1) for 2000/1999

State	Age in Years						Total
	12-17		18-25		26+
	Lower	Upper	Lower	Upper	Lower	Upper	Lower	Upper
Past Month Use of Marijuana
CA_TX (design-based)	0.83	1.19	0.75	1.12	0.73	1.54	0.82	1.22
CA_TX (avg. over substates)	0.68	1.49	0.64	1.32	0.62	2.08	0.73	1.47
NY_FL (design-based)	0.95	1.57	0.77	1.09	0.52	1.15	0.74	1.06
NY_FL (avg. over substates)	0.66	1.66	0.64	1.29	0.53	1.73	0.68	1.33
OH_MI (design-based)	0.83	1.27	0.89	1.30	0.74	1.60	0.87	1.32
OH_MI (avg. over substates)	0.67	1.61	0.76	1.47	0.61	1.90	0.78	1.44
PA_IL (design-based)	0.69	1.09	0.83	1.25	0.81	1.79	0.88	1.31
PA_IL (avg. over substates)	0.62	1.48	0.70	1.37	0.62	1.95	0.75	1.40
Past Year Use of Cocaine
CA_TX (design-based)	0.61	1.21	0.57	0.99	0.38	1.67	0.56	1.11
CA_TX (avg. over substates)	0.56	1.84	0.46	1.26	0.34	1.93	0.50	1.33
NY_FL (design-based)	0.41	1.63	0.58	1.03	0.53	1.71	0.61	1.26
NY_FL (avg. over substates)	0.44	1.93	0.48	1.44	0.29	1.54	0.42	1.28
OH_MI (design-based)	0.56	2.37	0.50	1.03	0.39	1.52	0.52	1.13
OH_MI (avg. over substates)	0.62	2.97	0.48	1.44	0.34	1.92	0.51	1.43
PA_IL (design-based)	0.48	1.46	0.70	1.42	0.65	2.31	0.75	1.63
PA_IL (avg. over substates)	0.50	2.28	0.53	1.64	0.58	3.01	0.68	1.95
Past Month "Binge" Alcohol Use
CA_TX (design-based)	0.80	1.12	0.85	1.02	0.90	1.23	0.90	1.14
CA_TX (avg. over substates)	0.72	1.37	0.77	1.13	0.79	1.39	0.83	1.26
NY_FL (design-based)	0.94	1.47	0.91	1.10	0.78	1.12	0.84	1.10
NY_FL (avg. over substates)	0.76	1.60	0.81	1.19	0.74	1.31	0.79	1.23
OH_MI (design-based)	1.01	1.41	0.99	1.18	0.81	1.04	0.88	1.06
OH_MI (avg. over substates)	0.80	1.60	0.91	1.29	0.75	1.26	0.83	1.22
PA_IL (design-based)	0.80	1.22	0.98	1.17	0.95	1.23	0.97	1.19
PA_IL (avg. over substates)	0.75	1.48	0.89	1.23	0.81	1.35	0.86	1.27
Past Month Use of Cigarettes
CA_TX (design-based)	0.82	1.10	0.79	1.01	0.96	1.28	0.94	1.18
CA_TX (avg. over substates)	0.68	1.23	0.74	1.09	0.83	1.39	0.84	1.26
NY_FL (design-based)	0.81	1.23	0.88	1.06	0.81	1.03	0.84	1.02
NY_FL (avg. over substates)	0.66	1.27	0.77	1.14	0.72	1.18	0.76	1.13
OH_MI (design-based)	0.76	1.02	0.86	1.03	0.80	1.02	0.83	1.00
OH_MI (avg. over substates)	0.66	1.18	0.83	1.14	0.72	1.13	0.77	1.09
PA_IL (design-based)	0.67	0.90	1.00	1.16	0.83	1.09	0.87	1.07
PA_IL (avg. over substates)	0.64	1.14	0.89	1.24	0.73	1.18	0.79	1.14

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.16 Ratio of Widths of 95 Percent Confidence Intervals of Change Estimates for 2000/1999

State	W1				W2				W3
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
Past Month Use of Marijuana
CA_TX	0.70	0.65	0.61	0.58	0.71	0.66	0.60	0.56	0.71	0.66	0.56	0.52
NY_FL	0.45	0.75	0.43	0.58	0.46	0.77	0.43	0.58	0.47	0.78	0.42	0.55
OH_MI	0.61	0.63	0.46	0.56	0.61	0.64	0.44	0.53	0.60	0.63	0.41	0.49
PA_IL	0.62	0.62	0.51	0.52	0.64	0.64	0.51	0.50	0.64	0.64	0.47	0.47
Average	0.59	0.66	0.50	0.56	0.60	0.68	0.50	0.54	0.61	0.68	0.47	0.51
Past Year Use of Cocaine
CA_TX	0.64	0.63	0.88	0.47	0.66	0.64	0.84	0.45	0.68	0.64	0.78	0.43
NY_FL	0.36	0.63	0.31	0.51	0.38	0.66	0.30	0.48	0.39	0.68	0.29	0.47
OH_MI	0.74	0.66	0.81	0.45	0.78	0.69	0.78	0.44	0.82	0.70	0.74	0.42
PA_IL	0.57	0.38	0.40	0.50	0.61	0.39	0.39	0.48	0.64	0.41	0.37	0.47
Average	0.58	0.57	0.60	0.48	0.61	0.60	0.57	0.46	0.63	0.61	0.54	0.45
Past Month "Binge" Alcohol Use
CA_TX	0.70	0.75	0.63	0.65	0.73	0.77	0.65	0.67	0.74	0.79	0.66	0.66
NY_FL	0.54	0.68	0.63	0.64	0.57	0.69	0.64	0.65	0.59	0.70	0.65	0.65
OH_MI	0.57	0.69	0.74	0.73	0.59	0.70	0.76	0.74	0.60	0.70	0.75	0.72
PA_IL	0.63	0.65	0.64	0.64	0.64	0.66	0.66	0.65	0.66	0.67	0.66	0.64
Average	0.61	0.69	0.66	0.67	0.63	0.71	0.68	0.68	0.65	0.72	0.68	0.67
Past Month Use of Cigarettes
CA_TX	0.64	0.75	0.60	0.61	0.66	0.77	0.63	0.64	0.68	0.79	0.66	0.66
NY_FL	0.53	0.66	0.68	0.67	0.56	0.68	0.71	0.70	0.59	0.71	0.74	0.72
OH_MI	0.70	0.74	0.68	0.68	0.73	0.76	0.71	0.71	0.77	0.79	0.74	0.73
PA_IL	0.72	0.70	0.64	0.65	0.75	0.72	0.66	0.67	0.76	0.74	0.69	0.68
Average	0.65	0.71	0.65	0.65	0.68	0.73	0.68	0.68	0.70	0.76	0.71	0.70
Overall	0.61	0.66	0.60	0.59	0.63	0.68	0.61	0.59	0.65	0.69	0.60	0.58

W1 = WR1 / WR, W2 = WR2 / WR, and W3 = WR3 / WR

where

WR1 = mean of widths of PIs of R1 over substates,
WR2 = mean of widths of PIs of R2 over substates,
WR3 = mean of widths of PIs of R3 over substates, and
WR = mean of widths of CIs of design-based estimate over substates.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.17 95 Percent Least Significant Lower and Upper Bounds of Change Estimates (R1) for 2000/1999

State	12-17		18-25		26+		Total
	Lower	Upper	Lower	Upper	Lower	Upper	Lower	Upper
Past Month Use of Marijuana
CA_TX	0.67	1.49	0.70	1.43	0.55	1.83	0.71	1.42
NY_FL	0.63	1.59	0.71	1.42	0.55	1.81	0.71	1.40
OH_MI	0.64	1.56	0.72	1.39	0.56	1.78	0.74	1.36
PA_IL	0.65	1.55	0.72	1.40	0.56	1.78	0.73	1.37
Average	0.65	1.54	0.71	1.41	0.56	1.80	0.72	1.39
Past Year Use of Cocaine
CA_TX	0.55	1.81	0.60	1.66	0.42	2.36	0.61	1.63
NY_FL	0.47	2.11	0.57	1.74	0.43	2.31	0.57	1.74
OH_MI	0.46	2.19	0.58	1.73	0.42	2.37	0.59	1.68
PA_IL	0.47	2.14	0.57	1.76	0.44	2.29	0.59	1.70
Average	0.49	2.06	0.58	1.72	0.43	2.33	0.59	1.69
Past Month "Binge" Alcohol Use
CA_TX	0.73	1.38	0.83	1.21	0.76	1.32	0.81	1.23
NY_FL	0.69	1.45	0.82	1.21	0.75	1.33	0.80	1.25
OH_MI	0.71	1.42	0.84	1.19	0.77	1.30	0.82	1.21
PA_IL	0.71	1.40	0.85	1.18	0.77	1.29	0.82	1.21
Average	0.71	1.41	0.84	1.20	0.76	1.31	0.82	1.23
Past Month Use of Cigarettes
CA_TX	0.74	1.35	0.82	1.22	0.77	1.30	0.82	1.22
NY_FL	0.72	1.39	0.82	1.22	0.78	1.28	0.82	1.22
OH_MI	0.75	1.34	0.85	1.17	0.80	1.26	0.84	1.19
PA_IL	0.75	1.34	0.85	1.18	0.79	1.27	0.83	1.20
Average	0.74	1.36	0.84	1.20	0.78	1.28	0.83	1.21

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.18 Past Month Use of Marijuana Based on Pooled 1999 and 2000 Data

State	Design-Based Estimates				SAE with Region				SAE Without Region
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
National	7.20	13.92	2.88	4.76	7.25	13.69	2.98	4.81	7.24	13.69	2.97	4.80
Northeast	7.57	17.74	3.05	5.24	7.69	17.50	3.11	5.26	7.87	16.77	3.23	5.29
Midwest	7.40	14.11	2.46	4.52	7.44	13.95	2.50	4.53	7.38	14.06	2.56	4.59
South	6.32	11.76	2.31	3.95	6.40	11.72	2.43	4.05	6.38	11.78	2.56	4.15
West	8.08	14.13	4.13	5.92	8.03	13.52	4.30	5.96	7.95	13.88	3.85	5.65
Alabama	7.02	11.12	1.43	3.26	6.49	11.24	2.19	3.80	6.40	11.18	2.27	3.84
Alaska	8.73	18.84	4.02	6.77	8.74	16.82	4.37	6.73	8.65	17.35	3.76	6.35
Arizona	8.00	10.09	3.46	4.85	7.47	11.05	3.48	4.93	7.48	11.40	2.89	4.53
Arkansas	7.96	11.06	1.88	3.71	7.10	9.93	2.30	3.78	7.09	10.00	2.43	3.89
California	7.60	13.94	4.16	5.86	7.56	13.16	4.35	5.90	7.50	13.49	4.02	5.69
Colorado	11.75	22.47	5.30	8.24	10.97	19.91	5.73	8.14	10.80	20.49	5.21	7.80
Connecticut	10.85	17.10	3.16	5.47	9.79	18.38	3.35	5.66	9.99	17.05	3.57	5.70
Delaware	13.50	21.05	3.51	6.70	12.00	20.83	4.07	6.93	11.89	20.81	4.48	7.24
District of Columbia	7.21	11.83	2.89	4.53	7.24	12.40	3.74	5.25	7.25	12.48	3.69	5.23
Florida	6.33	13.31	3.39	4.73	6.68	13.05	3.29	4.65	6.63	13.11	3.40	4.74
Georgia	5.44	11.22	3.79	4.97	5.85	11.85	2.68	4.25	5.89	12.01	2.91	4.45
Hawaii	10.07	14.67	5.78	7.26	8.86	13.65	4.86	6.30	8.72	14.35	4.48	6.07
Idaho	5.01	10.33	2.85	4.25	6.00	10.83	2.96	4.52	5.99	11.12	2.36	4.12
Illinois	8.57	14.31	2.51	4.70	8.18	14.18	2.62	4.73	8.13	14.25	2.67	4.77
Indiana	7.70	11.87	3.11	4.76	7.50	12.09	2.54	4.33	7.48	12.26	2.65	4.43
Iowa	3.71	9.27	1.24	2.57	4.88	9.29	1.40	2.81	4.94	9.43	1.34	2.79
Kansas	6.93	12.18	1.38	3.46	6.85	12.03	1.77	3.71	6.82	12.00	1.74	3.68
Kentucky	6.50	13.30	1.74	3.76	6.80	12.55	2.26	4.07	6.79	12.71	2.41	4.21
Louisiana	6.53	11.00	1.63	3.57	6.10	11.17	1.76	3.64	6.07	11.19	1.89	3.74
Maine	8.61	21.37	3.25	5.88	9.01	21.40	3.27	5.93	9.25	20.31	3.42	5.95
Maryland	9.23	12.61	1.59	3.64	8.39	13.13	2.54	4.37	8.25	13.23	2.66	4.46
Massachusetts	13.30	26.58	6.96	9.90	12.20	26.01	5.79	8.77	12.35	24.81	6.28	9.03
Michigan	7.77	16.64	3.53	5.68	8.01	16.54	3.34	5.55	7.94	16.61	3.49	5.66
Minnesota	10.72	14.62	1.71	4.44	9.24	14.97	2.25	4.71	9.13	15.08	2.27	4.73
Mississippi	5.17	11.63	0.49	2.62	5.28	10.63	1.33	3.11	5.28	10.67	1.40	3.16
Missouri	5.84	14.28	1.92	3.95	6.62	13.40	2.38	4.26	6.55	13.62	2.45	4.33
Montana	10.51	15.71	2.41	5.01	9.42	14.80	3.10	5.30	9.26	15.05	2.55	4.89
Nebraska	5.64	11.42	1.19	3.09	6.16	11.55	1.65	3.50	6.17	11.54	1.57	3.45
Nevada	10.05	14.58	3.65	5.55	9.72	13.21	4.15	5.75	9.54	13.73	3.54	5.31
New Hampshire	11.20	18.56	2.87	5.59	10.54	19.95	3.26	5.98	10.73	18.74	3.39	5.96
New Jersey	6.01	16.79	2.37	4.39	6.63	15.86	2.81	4.69	6.81	14.88	2.86	4.63
New Mexico	10.52	15.95	3.55	6.12	9.74	14.86	4.13	6.30	9.52	15.15	3.60	5.93
New York	6.32	16.77	2.02	4.26	6.64	16.26	2.38	4.51	6.83	15.79	2.42	4.50
North Carolina	5.76	15.34	4.16	5.69	6.53	14.29	3.71	5.29	6.51	14.35	3.98	5.50
North Dakota	7.41	10.20	0.57	2.75	6.80	10.27	1.38	3.27	6.80	10.16	1.27	3.17
Ohio	6.07	14.31	2.49	4.40	6.46	13.66	2.38	4.26	6.44	13.77	2.41	4.30
Oklahoma	5.13	7.69	1.36	2.63	5.58	8.39	1.64	2.98	5.66	8.39	1.68	3.02
Oregon	8.83	17.37	4.17	6.28	9.48	17.16	4.95	6.90	9.39	17.68	4.40	6.53
Pennsylvania	5.83	14.16	2.79	4.42	6.28	14.43	2.74	4.45	6.46	13.96	2.81	4.47
Rhode Island	9.17	23.20	4.77	7.32	10.20	22.71	4.33	7.00	10.35	21.79	4.70	7.20
South Carolina	6.41	12.03	1.98	3.68	6.57	12.46	2.21	3.93	6.54	12.49	2.33	4.02
South Dakota	7.04	10.14	1.91	3.69	6.49	11.37	1.84	3.72	6.50	11.37	1.85	3.73
Tennessee	6.49	11.13	2.41	3.94	6.61	11.14	2.72	4.17	6.57	11.23	2.88	4.31
Texas	6.00	10.41	1.34	3.22	5.91	10.32	1.51	3.32	5.92	10.34	1.56	3.36
Utah	4.02	5.77	2.01	3.01	4.85	7.34	2.27	3.59	4.85	7.44	1.58	3.15
Vermont	11.23	26.28	3.99	7.48	10.50	25.65	3.79	7.18	10.62	24.60	4.05	7.26
Virginia	5.06	11.54	2.25	3.67	5.83	12.31	2.43	3.98	5.82	12.50	2.60	4.13
Washington	8.40	14.47	5.05	6.58	8.83	13.96	4.50	6.14	8.70	14.28	3.80	5.62
West Virginia	8.32	10.86	0.72	2.70	7.39	10.57	1.89	3.48	7.32	10.67	1.90	3.49
Wisconsin	8.05	16.30	2.69	5.10	8.20	16.31	2.70	5.09	8.08	16.60	2.86	5.24
Wyoming	7.28	13.08	2.50	4.58	7.51	12.69	2.91	4.85	7.42	12.99	2.26	4.40

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.19 Past Year Use of Cocaine Based on Pooled 1999 and 2000 Data

State	Design-Based Estimates				SAE with Region				SAE Without Region
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
National	1.63	4.82	1.04	1.59	1.67	4.73	1.13	1.65	1.67	4.73	1.12	1.64
Northeast	1.16	4.56	1.16	1.56	1.18	4.55	1.27	1.65	1.43	4.63	1.09	1.54
Midwest	1.16	4.65	0.80	1.35	1.18	4.48	0.86	1.37	1.42	4.50	1.00	1.50
South	1.75	4.75	1.04	1.60	1.80	4.72	1.13	1.66	1.66	4.74	1.19	1.70
West	2.32	5.28	1.18	1.86	2.35	5.14	1.28	1.92	2.13	5.03	1.18	1.80
Alabama	2.36	3.88	1.12	1.60	1.71	4.13	1.28	1.69	1.54	4.17	1.38	1.76
Alaska	0.92	5.39	2.38	2.63	1.93	5.36	1.86	2.37	1.62	5.17	1.71	2.20
Arizona	4.05	6.70	1.36	2.37	3.41	6.12	1.43	2.27	3.15	5.98	1.27	2.11
Arkansas	1.26	3.63	1.07	1.42	1.62	3.70	1.12	1.50	1.44	3.72	1.15	1.51
California	2.05	4.79	1.29	1.85	2.14	4.73	1.26	1.83	2.00	4.67	1.16	1.73
Colorado	2.93	10.88	1.31	2.74	2.74	8.98	1.54	2.64	2.42	8.73	1.38	2.45
Connecticut	1.32	2.94	1.19	1.40	1.22	4.27	1.31	1.64	1.55	4.43	1.08	1.51
Delaware	1.79	5.75	3.98	3.98	1.75	6.05	2.08	2.53	1.62	6.10	2.02	2.48
District of Columbia	1.50	4.30	2.10	2.34	1.01	4.14	1.87	2.09	0.89	4.12	1.88	2.08
Florida	1.52	5.96	1.18	1.73	1.70	5.32	1.14	1.64	1.58	5.31	1.22	1.69
Georgia	1.13	5.29	1.40	1.90	1.33	4.82	1.25	1.74	1.20	4.80	1.33	1.79
Hawaii	1.20	4.93	1.69	2.03	1.86	3.93	1.72	1.99	1.61	3.72	1.54	1.81
Idaho	2.06	2.54	0.36	0.90	2.20	3.56	0.84	1.42	1.86	3.51	0.79	1.33
Illinois	0.96	3.93	1.11	1.47	1.08	4.12	0.97	1.40	1.28	4.13	1.08	1.51
Indiana	1.66	4.88	0.23	1.00	1.34	4.55	0.67	1.26	1.64	4.61	0.85	1.43
Iowa	1.00	3.79	0.59	1.06	1.19	4.05	0.72	1.21	1.44	4.07	0.83	1.33
Kansas	0.16	4.26	0.63	1.07	1.01	4.33	0.82	1.31	1.22	4.41	0.99	1.48
Kentucky	0.99	5.27	0.80	1.41	1.63	5.02	1.11	1.68	1.45	4.99	1.12	1.66
Louisiana	1.21	3.93	1.16	1.57	1.31	4.02	1.29	1.69	1.17	4.05	1.34	1.71
Maine	2.21	3.41	0.69	1.16	1.55	3.90	0.97	1.37	1.92	4.06	0.83	1.31
Maryland	1.79	3.09	0.61	1.02	1.51	3.82	0.88	1.29	1.35	3.80	0.90	1.29
Massachusetts	1.10	6.89	2.52	2.90	1.28	6.32	1.77	2.25	1.63	6.44	1.46	2.06
Michigan	1.02	5.04	0.86	1.42	1.09	4.69	0.91	1.42	1.27	4.68	1.04	1.54
Minnesota	2.39	4.82	1.03	1.69	1.63	4.90	0.84	1.47	2.02	4.88	1.01	1.64
Mississippi	1.07	3.82	0.44	1.00	1.21	3.84	1.02	1.44	1.06	3.84	1.11	1.49
Missouri	0.75	3.57	0.45	0.89	1.03	3.79	0.75	1.17	1.27	3.84	0.87	1.30
Montana	3.03	5.32	0.40	1.32	2.64	5.13	0.90	1.63	2.28	4.95	0.86	1.54
Nebraska	0.86	4.32	0.52	1.08	1.18	4.42	0.74	1.29	1.46	4.42	0.88	1.43
Nevada	2.61	6.72	1.14	1.94	2.47	5.81	1.72	2.27	2.10	5.53	1.64	2.14
New Hampshire	1.92	5.39	0.39	1.14	1.46	4.83	0.90	1.42	1.82	4.99	0.80	1.40
New Jersey	0.76	4.77	0.91	1.35	1.03	4.58	1.21	1.59	1.27	4.71	1.01	1.47
New Mexico	3.22	8.49	2.01	3.07	3.49	7.52	1.95	2.92	3.19	7.33	1.84	2.77
New York	1.18	3.87	1.01	1.37	1.16	4.04	1.27	1.60	1.38	4.10	1.10	1.49
North Carolina	1.65	3.77	1.12	1.50	1.57	4.15	1.19	1.59	1.41	4.19	1.20	1.59
North Dakota	1.42	3.89	0.20	0.87	1.34	3.88	0.64	1.18	1.62	3.91	0.77	1.31
Ohio	0.78	4.98	0.92	1.43	0.99	4.54	0.93	1.40	1.16	4.53	1.05	1.51
Oklahoma	1.05	3.21	0.70	1.07	1.60	3.79	1.03	1.46	1.39	3.77	1.08	1.47
Oregon	1.98	4.70	0.69	1.32	2.14	4.82	1.08	1.65	1.83	4.65	0.97	1.51
Pennsylvania	1.18	4.39	1.00	1.41	1.16	4.31	1.13	1.50	1.37	4.37	1.00	1.43
Rhode Island	0.72	7.25	0.84	1.56	1.16	5.83	1.29	1.79	1.47	5.96	1.11	1.69
South Carolina	1.52	3.86	0.96	1.38	1.45	4.17	1.15	1.55	1.31	4.20	1.26	1.63
South Dakota	2.35	5.73	0.26	1.28	1.79	4.62	0.72	1.39	2.20	4.63	0.87	1.56
Tennessee	2.08	2.64	2.18	2.23	1.84	3.84	1.50	1.83	1.67	3.89	1.49	1.81
Texas	2.66	6.10	0.83	1.82	2.64	5.69	1.01	1.89	2.56	5.72	1.10	1.95
Utah	1.62	2.31	0.44	0.97	2.01	3.54	0.91	1.56	1.68	3.42	0.90	1.48
Vermont	1.49	7.62	1.16	1.98	1.40	6.21	1.22	1.84	1.77	6.36	1.05	1.77
Virginia	1.29	4.70	0.41	1.02	1.46	4.76	0.96	1.47	1.30	4.77	1.00	1.49
Washington	2.46	4.04	0.82	1.39	2.34	4.49	1.05	1.62	2.02	4.35	0.95	1.49
West Virginia	1.60	3.47	0.52	0.99	1.84	3.78	0.84	1.30	1.62	3.81	0.86	1.30
Wisconsin	1.78	6.19	0.99	1.77	1.49	5.42	0.92	1.58	1.82	5.50	1.06	1.73
Wyoming	1.58	4.78	0.61	1.32	2.01	4.89	0.96	1.65	1.68	4.68	0.89	1.53

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.20 Past Month Use of Alcohol Based on Pooled 1999 and 2000 Data

State	Design-Based Estimates				SAE with Region				SAE Without Region
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
National	16.45	57.04	48.88	46.53	16.40	56.82	48.55	46.26	16.40	56.81	48.55	46.25
Northeast	18.08	62.76	54.04	51.56	18.12	63.08	54.14	51.69	17.90	62.40	54.28	51.70
Midwest	17.25	62.68	51.70	49.51	17.18	62.39	50.54	48.59	17.34	62.27	50.33	48.44
South	15.47	53.06	42.45	40.99	15.37	52.84	42.16	40.73	15.25	52.91	42.82	41.23
West	15.88	52.91	51.73	47.95	15.85	52.38	51.84	47.96	16.05	52.86	50.82	47.28
Alabama	14.94	51.25	37.42	36.93	14.60	50.18	36.23	35.84	14.46	50.18	37.59	36.87
Alaska	16.41	56.82	59.59	53.66	16.35	57.28	58.91	53.23	16.57	58.13	58.22	52.87
Arizona	17.09	53.66	54.13	49.90	16.77	54.42	49.92	46.78	17.06	54.95	49.22	46.36
Arkansas	19.11	46.94	36.37	35.93	17.69	46.38	35.12	34.75	17.34	46.23	35.92	35.32
California	15.50	51.77	50.36	46.71	15.50	51.06	50.86	46.99	15.56	51.28	50.15	46.49
Colorado	19.90	70.64	63.21	59.61	19.76	66.83	63.76	59.53	20.08	68.16	62.15	58.51
Connecticut	22.03	67.20	57.74	55.43	21.07	68.19	58.98	56.47	20.58	67.17	58.61	56.01
Delaware	19.33	59.55	55.60	52.37	18.35	60.80	54.58	51.65	17.82	60.83	55.69	52.46
District of Columbia	12.79	56.79	47.05	44.86	12.30	54.46	47.40	44.75	12.19	54.78	47.55	44.90
Florida	14.29	54.97	49.41	46.74	14.49	54.54	48.18	45.73	14.37	54.52	48.63	46.08
Georgia	15.25	51.36	44.32	42.17	15.21	51.99	44.52	42.40	15.08	52.12	45.60	43.23
Hawaii	18.06	53.19	47.56	45.34	16.69	53.32	45.70	43.76	16.83	54.25	44.93	43.28
Idaho	13.26	45.80	44.71	41.07	13.87	46.71	45.86	42.14	14.26	47.38	44.83	41.54
Illinois	18.57	60.45	52.50	50.08	17.93	60.94	53.43	50.79	18.05	60.88	53.25	50.66
Indiana	12.36	57.54	43.45	42.11	13.20	54.87	41.21	40.13	13.54	54.63	40.62	39.69
Iowa	18.14	72.11	54.93	53.35	19.08	70.09	52.58	51.41	19.31	70.01	52.82	51.60
Kansas	16.21	59.50	51.88	48.90	15.92	60.52	50.39	47.90	16.15	59.84	49.92	47.48
Kentucky	14.37	53.65	31.89	33.01	14.72	52.77	33.36	34.05	14.65	52.98	33.81	34.41
Louisiana	20.91	57.09	44.38	43.45	19.81	57.60	43.99	43.13	19.44	57.94	44.99	43.88
Maine	19.57	66.12	50.37	49.15	19.59	65.57	51.67	50.12	19.42	64.98	51.49	49.90
Maryland	16.73	58.43	50.50	48.12	15.83	57.64	52.02	49.13	15.70	58.01	52.11	49.23
Massachusetts	22.64	72.54	64.18	61.11	22.45	72.50	62.94	60.14	21.94	71.74	63.35	60.33
Michigan	16.76	62.59	49.83	48.01	16.59	61.81	48.81	47.11	16.70	61.71	48.65	46.99
Minnesota	18.87	70.14	57.10	54.66	18.73	70.34	56.15	53.97	18.88	70.30	55.86	53.76
Mississippi	13.74	44.82	29.16	29.62	13.52	43.60	28.99	29.28	13.50	43.48	29.75	29.83
Missouri	15.74	58.28	46.88	45.09	15.77	59.29	46.91	45.24	16.06	58.94	46.37	44.81
Montana	22.06	64.60	60.06	56.45	21.80	63.29	59.72	56.01	22.00	64.31	58.61	55.32
Nebraska	18.27	71.64	55.17	53.26	18.71	71.40	54.32	52.69	19.03	71.32	53.95	52.44
Nevada	18.56	56.27	57.20	53.40	17.51	56.68	57.14	53.30	17.89	57.53	56.10	52.62
New Hampshire	21.83	65.03	62.06	58.22	21.72	68.70	59.95	57.01	21.15	67.38	60.50	57.23
New Jersey	18.44	60.22	54.05	51.45	18.00	60.28	54.39	51.68	17.69	58.95	54.36	51.47
New Mexico	17.79	58.97	57.04	52.70	18.41	56.98	55.34	51.22	18.60	58.00	54.71	50.92
New York	17.25	60.82	51.58	49.31	17.30	60.87	51.74	49.44	17.18	60.39	51.92	49.51
North Carolina	12.66	53.66	35.37	35.28	13.00	52.63	37.21	36.62	12.93	52.77	37.69	37.01
North Dakota	27.90	79.70	57.52	57.22	26.15	76.04	58.32	57.08	26.21	76.27	57.75	56.69
Ohio	15.55	59.46	49.10	47.00	15.67	59.01	47.23	45.52	15.81	58.97	47.20	45.50
Oklahoma	14.91	52.33	35.51	35.43	14.59	51.09	36.62	36.07	14.46	51.18	37.35	36.62
Oregon	14.91	58.31	52.99	49.90	15.45	57.86	53.86	50.63	15.88	58.92	52.17	49.48
Pennsylvania	15.24	60.27	50.42	48.14	15.84	60.80	50.92	48.65	15.79	60.47	51.09	48.74
Rhode Island	16.87	64.11	58.04	54.56	18.03	66.25	55.47	52.93	17.65	65.13	55.89	53.10
South Carolina	13.51	46.54	39.05	37.31	13.55	47.19	36.18	35.19	13.31	47.07	37.15	35.89
South Dakota	19.89	69.38	55.11	52.91	19.81	69.77	51.86	50.55	20.02	69.60	52.00	50.66
Tennessee	13.36	43.32	32.93	32.31	13.25	44.92	33.73	33.11	13.10	44.79	34.67	33.81
Texas	17.98	54.73	44.86	43.15	17.73	54.62	44.39	42.76	17.70	54.66	44.76	43.04
Utah	9.50	29.49	28.86	26.15	10.00	32.31	32.71	29.36	10.62	32.66	30.55	28.07
Vermont	19.34	69.47	60.31	57.02	20.02	68.63	59.46	56.38	19.63	67.87	59.79	56.50
Virginia	10.76	58.64	49.25	46.57	12.26	57.77	47.36	45.14	12.24	57.91	48.40	45.96
Washington	14.90	50.23	52.12	48.07	14.82	50.20	52.48	48.33	15.10	50.60	50.69	47.03
West Virginia	17.33	46.46	31.92	32.42	16.20	48.16	32.00	32.59	16.03	48.09	32.18	32.70
Wisconsin	21.94	68.25	64.33	60.22	21.47	68.97	60.17	57.15	21.46	68.92	60.29	57.24
Wyoming	21.45	64.93	52.83	50.90	20.53	62.03	54.02	51.27	21.00	63.32	52.28	50.22

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.21 Past Month Use of Cigarettes Based on Pooled 1999 and 2000 Data

State	Design-Based Estimates				SAE with Region				SAE Without Region
	12-17	18-25	26+	Total	12-17	18-25	26+	Total	12-17	18-25	26+	Total
National	14.16	38.97	24.57	25.34	14.15	38.68	24.60	25.33	14.15	38.69	24.59	25.32
Northeast	14.28	40.17	23.38	24.49	14.36	39.56	23.37	24.41	14.20	39.44	23.83	24.74
Midwest	16.13	44.60	25.90	27.35	16.10	44.33	25.97	27.35	16.21	44.00	25.74	27.15
South	14.72	38.01	25.49	25.98	14.65	37.86	25.59	26.03	14.49	37.94	25.64	26.06
West	11.22	33.67	22.73	22.94	11.23	33.42	22.63	22.83	11.47	33.77	22.34	22.69
Alabama	16.09	34.65	25.86	26.01	15.99	35.86	26.32	26.51	15.81	35.90	26.45	26.60
Alaska	15.80	44.44	24.55	26.31	15.95	43.10	23.29	25.22	16.37	43.83	23.13	25.26
Arizona	13.59	40.43	23.08	24.31	13.49	38.97	23.41	24.36	13.95	39.60	23.04	24.21
Arkansas	20.59	36.13	28.64	28.77	18.89	37.20	28.47	28.60	18.56	37.29	28.35	28.48
California	8.73	29.62	22.07	21.62	8.76	29.65	21.84	21.45	8.85	29.78	21.58	21.29
Colorado	18.13	45.29	22.90	25.35	16.62	43.20	23.40	25.28	17.17	44.01	23.17	25.27
Connecticut	18.87	43.50	21.06	23.40	16.90	42.29	21.74	23.62	16.63	42.18	22.40	24.11
Delaware	17.77	45.50	25.13	26.89	15.55	43.65	25.75	26.91	15.39	43.72	25.78	26.93
District of Columbia	9.05	33.27	25.17	24.61	10.15	32.20	25.23	24.62	9.90	32.42	25.28	24.66
Florida	10.92	34.60	25.16	24.85	11.41	34.87	25.26	25.00	11.30	34.96	25.23	24.98
Georgia	14.54	37.33	27.21	27.23	14.37	37.23	26.34	26.53	14.19	37.29	26.45	26.60
Hawaii	11.95	39.86	22.32	23.40	11.47	38.76	21.38	22.47	12.05	39.63	21.14	22.45
Idaho	10.86	35.30	23.15	23.51	12.31	35.76	23.45	23.98	12.64	36.28	23.14	23.87
Illinois	15.61	43.44	25.57	26.93	15.44	43.13	25.62	26.91	15.54	42.94	25.46	26.77
Indiana	17.40	41.86	26.03	27.26	16.18	41.73	26.72	27.63	16.28	41.31	26.24	27.22
Iowa	17.03	42.70	25.49	26.89	16.76	43.36	24.39	26.11	16.89	42.87	24.02	25.77
Kansas	11.82	39.50	23.55	24.38	13.60	40.19	23.31	24.49	13.66	39.62	22.97	24.16
Kentucky	23.42	47.03	32.57	33.57	22.58	46.89	31.34	32.51	22.42	47.01	31.32	32.49
Louisiana	15.12	40.44	27.79	28.13	15.03	40.02	27.22	27.66	14.92	40.05	27.21	27.63
Maine	15.48	45.99	25.41	26.82	17.04	44.96	24.77	26.34	16.72	44.67	25.23	26.64
Maryland	15.89	34.40	21.41	22.40	14.25	34.89	22.80	23.39	14.04	35.06	22.84	23.42
Massachusetts	15.59	42.50	21.65	23.52	15.69	41.48	22.22	23.84	15.49	41.33	22.84	24.29
Michigan	15.68	43.81	25.14	26.57	15.82	43.54	26.01	27.22	15.88	43.29	25.88	27.09
Minnesota	19.87	49.38	25.84	28.36	19.14	48.88	24.63	27.28	19.34	48.36	24.35	27.02
Mississippi	14.93	33.45	26.85	26.43	15.04	33.61	27.36	26.83	14.79	33.65	27.39	26.83
Missouri	14.06	46.38	30.55	30.88	14.91	45.98	28.62	29.43	15.09	45.62	28.29	29.15
Montana	17.68	41.29	21.91	23.94	17.05	40.90	22.32	24.13	17.47	41.39	22.10	24.07
Nebraska	12.48	44.69	20.10	22.61	13.77	43.52	21.23	23.45	13.91	43.01	20.90	23.14
Nevada	17.31	41.30	30.51	30.52	15.85	40.35	28.98	29.07	16.42	41.27	28.77	29.07
New Hampshire	15.67	41.56	24.68	25.73	16.04	42.65	23.67	25.12	15.76	42.35	24.15	25.43
New Jersey	12.75	41.71	21.11	22.73	12.68	39.79	21.63	22.91	12.58	39.67	22.24	23.37
New Mexico	15.06	42.85	22.76	24.70	15.33	40.45	23.74	25.11	15.80	41.19	23.73	25.26
New York	12.28	36.29	23.95	24.31	12.38	36.20	23.72	24.13	12.25	36.08	24.09	24.39
North Carolina	17.85	45.13	26.34	27.77	17.41	43.80	26.87	27.97	17.29	44.04	27.03	28.11
North Dakota	21.34	47.22	24.46	27.35	20.50	46.50	23.76	26.59	20.61	46.03	23.65	26.46
Ohio	15.83	45.66	28.21	29.21	15.79	44.99	28.28	29.17	15.89	44.87	28.18	29.09
Oklahoma	13.51	43.56	29.91	29.88	15.25	42.66	27.97	28.50	14.95	42.67	28.07	28.54
Oregon	14.42	43.04	23.06	24.70	14.66	41.42	23.99	25.24	15.03	41.99	23.61	25.05
Pennsylvania	16.21	42.32	24.97	26.14	16.55	41.93	24.72	25.93	16.44	41.88	25.08	26.20
Rhode Island	12.94	37.18	27.36	27.02	14.27	37.50	25.99	26.11	14.03	37.25	26.40	26.39
South Carolina	16.47	35.01	23.95	24.54	15.68	35.42	25.51	25.71	15.49	35.46	25.54	25.72
South Dakota	19.36	45.25	21.87	24.86	18.90	45.11	22.44	25.19	18.95	44.60	22.22	24.96
Tennessee	16.88	45.67	26.87	28.28	17.35	44.17	26.87	28.12	17.15	44.38	27.02	28.24
Texas	12.73	34.49	23.12	23.57	12.73	34.67	23.23	23.68	12.59	34.67	23.26	23.68
Utah	8.33	22.37	12.81	13.96	9.82	24.61	17.12	17.46	10.05	24.75	16.91	17.39
Vermont	14.40	44.69	22.61	24.42	14.72	43.94	22.13	24.01	14.49	43.66	22.59	24.30
Virginia	12.85	39.23	22.00	23.19	13.31	38.26	22.90	23.83	13.13	38.41	22.92	23.84
Washington	12.69	32.80	26.02	25.51	13.12	33.88	24.13	24.23	13.44	34.42	23.54	23.87
West Virginia	19.75	46.11	30.03	31.12	20.06	45.35	29.21	30.40	19.90	45.55	29.34	30.51
Wisconsin	17.60	46.43	22.00	24.79	17.58	46.63	23.72	26.09	17.70	45.96	23.46	25.81
Wyoming	16.30	42.58	23.32	25.28	15.79	42.06	23.87	25.54	16.20	42.83	23.67	25.55

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.22 Relative Absolute Bias for Past Month Use of Marijuana Based on Pooled 1999 and 2000 Data

State	Age in Years			Total
	12-17	18-25	26+
CA (design-based)	7.60	13.94	4.16	5.86
CA1	7.30	14.22	5.26	6.70
CA2	7.69	13.28	3.41	5.22
CA3	7.34	13.53	3.08	4.96
CA4	7.53	12.78	3.34	5.09
Average across 4 substates	7.47	13.45	3.77	5.49
Relative Absolute Bias	1.75	3.54	9.28	6.35
FL (design-based)	6.33	13.31	3.39	4.73
FL1	7.39	14.64	3.59	5.13
FL2	7.51	11.76	3.68	4.90
FL3	5.66	13.22	3.10	4.42
FL4	6.63	13.52	3.71	5.03
Average across 4 substates	6.80	13.28	3.52	4.87
Relative Absolute Bias	7.39	0.19	3.77	3.02
IL (design-based)	8.57	14.31	2.51	4.70
IL1	7.41	17.15	3.02	5.35
IL2	8.27	14.36	2.85	4.93
IL3	6.83	12.49	2.46	4.24
IL4	8.25	13.82	2.66	4.72
Average across 4 substates	7.69	14.45	2.75	4.81
Relative Absolute Bias	10.24	1.01	9.66	2.44
MI (design-based)	7.77	16.64	3.53	5.68
MI1	7.85	18.00	3.40	5.77
MI2	7.90	17.12	3.48	5.72
MI3	7.77	16.17	3.34	5.48
MI4	8.51	16.37	3.37	5.60
Average across 4 substates	8.01	16.92	3.40	5.64
Relative Absolute Bias	3.08	1.69	3.71	0.68
NY (design-based)	6.32	16.77	2.02	4.26
NY1	7.29	14.69	2.54	4.51
NY2	7.06	15.60	2.70	4.72
NY3	7.38	15.26	2.85	4.82
NY4	6.61	15.98	2.40	4.49
Average across 4 substates	7.08	15.38	2.62	4.63
Relative Absolute Bias	12.08	8.26	29.53	8.69
OH (design-based)	6.07	14.31	2.49	4.40
OH1	5.92	13.31	2.21	4.04
OH2	6.83	13.14	2.57	4.38
OH3	7.00	14.75	2.60	4.63
OH4	6.98	14.72	2.37	4.45
Average across 4 substates	6.68	13.98	2.44	4.38
Relative Absolute Bias	10.03	2.31	2.17	0.50
PA (design-based)	5.83	14.16	2.79	4.42
PA1	7.45	14.49	3.13	4.88
PA2	6.33	12.47	2.40	3.96
PA3	6.37	13.12	2.58	4.18
PA4	7.11	15.58	2.88	4.78
Average across 4 substates	6.81	13.91	2.75	4.45
Relative Absolute Bias	16.90	1.75	1.63	0.71
TX (design-based)	6.00	10.41	1.34	3.22
TX1	5.99	9.27	1.63	3.26
TX2	6.01	11.52	1.86	3.77
TX3	6.06	10.75	1.84	3.64
TX4	5.29	10.83	1.77	3.51
Average across 4 substates	5.84	10.59	1.77	3.55
Relative Absolute Bias	2.65	1.79	32.35	10.19
Average Relative Absolute Bias	8.01	2.57	11.51	4.07

Note: Relative Absolute Bias = 100 × abs(Average SAE over 4 substates - Large State design-based estimate) / Large State design-based estimate.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.23 Relative Absolute Bias for Past Year Use of Cocaine Based on Pooled 1999 and 2000 Data

State	Age in Years			Total
	12-17	18-25	26+
CA (design-based)	2.05	4.79	1.29	1.85
CA1	1.86	4.21	0.99	1.52
CA2	1.82	4.81	1.00	1.61
CA3	2.20	5.43	1.63	2.21
CA4	2.13	4.58	1.06	1.65
Average across 4 substates	2.00	4.76	1.17	1.75
Relative Absolute Bias	2.19	0.65	9.24	5.36
FL (design-based)	1.52	5.96	1.18	1.73
FL1	1.72	5.56	1.49	1.95
FL2	1.53	4.13	1.01	1.40
FL3	1.55	5.18	1.20	1.66
FL4	1.42	4.58	1.10	1.50
Average across 4 substates	1.55	4.86	1.20	1.63
Relative Absolute Bias	2.18	18.43	1.60	5.78
IL (design-based)	0.96	3.93	1.11	1.47
IL1	1.32	4.42	1.06	1.53
IL2	1.49	4.88	1.19	1.71
IL3	1.61	4.50	0.98	1.52
IL4	1.24	3.66	1.07	1.43
Average across 4 substates	1.41	4.36	1.08	1.55
Relative Absolute Bias	47.60	10.97	2.88	5.43
MI (design-based)	1.02	5.04	0.86	1.42
MI1	1.27	5.32	1.22	1.76
MI2	1.46	4.34	1.04	1.51
MI3	1.38	4.54	1.00	1.50
MI4	1.53	4.68	1.25	1.72
Average across 4 substates	1.41	4.72	1.13	1.62
Relative Absolute Bias	38.23	6.34	30.39	14.07
NY (design-based)	1.18	3.87	1.01	1.37
NY1	1.31	4.08	1.07	1.46
NY2	1.41	4.70	1.08	1.56
NY3	1.71	4.52	1.05	1.54
NY4	1.41	3.90	1.20	1.55
Average across 4 substates	1.46	4.30	1.10	1.53
Relative Absolute Bias	23.10	11.10	9.67	11.32
OH (design-based)	0.78	4.98	0.92	1.43
OH1	1.26	4.72	1.18	1.65
OH2	1.32	4.32	1.03	1.49
OH3	1.40	5.03	1.04	1.59
OH4	1.31	4.64	1.05	1.54
Average across 4 substates	1.32	4.68	1.07	1.57
Relative Absolute Bias	69.04	6.15	17.00	9.45
PA (design-based)	1.18	4.39	1.00	1.41
PA1	1.50	4.13	1.01	1.42
PA2	1.24	4.33	0.82	1.27
PA3	1.55	4.73	1.18	1.63
PA4	1.59	5.10	1.06	1.58
Average across 4 substates	1.47	4.57	1.02	1.48
Relative Absolute Bias	25.11	4.01	1.71	4.45
TX (design-based)	2.66	6.10	0.83	1.82
TX1	2.48	5.43	1.04	1.85
TX2	2.15	5.69	1.19	1.96
TX3	2.29	5.34	1.21	1.94
TX4	2.35	5.73	1.26	2.04
Average across 4 substates	2.32	5.54	1.17	1.95
Relative Absolute Bias	12.90	9.07	41.21	7.17
Average Relative Absolute Bias	27.54	8.34	14.21	7.88

Note: Relative Absolute Bias = 100 × abs(Average SAE over 4 substates - Large State design-based estimate) / Large State design-based estimate.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.24 Relative Absolute Bias for Past Month "Binge" Alcohol Use Based on Pooled 1999 and 2000 Data

State	Age in Years			Total
	12-17	18-25	26+
CA (design-based)	9.12	32.46	18.58	19.42
CA1	9.01	31.04	18.40	19.08
CA2	8.50	30.35	17.77	18.45
CA3	9.77	35.11	19.18	20.30
CA4	9.35	32.13	18.83	19.59
Average across 4 substates	9.16	32.16	18.55	19.36
Relative Absolute Bias	0.40	0.93	0.18	0.32
FL (design-based)	7.93	35.02	17.72	18.67
FL1	8.56	34.49	17.41	18.42
FL2	9.49	32.97	17.82	18.67
FL3	8.30	34.20	17.06	18.08
FL4	8.83	37.06	18.13	19.29
Average across 4 substates	8.79	34.68	17.60	18.62
Relative Absolute Bias	10.94	0.97	0.68	0.28
IL (design-based)	11.53	41.83	21.43	23.13
IL1	9.98	41.10	19.09	21.08
IL2	12.38	43.38	22.76	24.44
IL3	10.39	40.60	20.69	22.28
IL4	11.25	41.42	21.46	23.07
Average across 4 substates	11.00	41.62	21.00	22.72
Relative Absolute Bias	4.60	0.50	2.00	1.77
MI (design-based)	10.88	42.23	19.08	21.23
MI1	9.65	40.35	18.37	20.31
MI2	11.00	41.60	19.54	21.51
MI3	10.68	41.86	20.57	22.30
MI4	12.03	40.64	19.72	21.63
Average across 4 substates	10.84	41.12	19.55	21.44
Relative Absolute Bias	0.38	2.64	2.47	1.00
NY (design-based)	10.14	39.47	18.61	20.33
NY1	8.99	34.89	18.74	19.76
NY2	9.35	42.29	18.54	20.54
NY3	10.66	40.54	19.07	20.87
NY4	10.68	38.23	18.62	20.24
Average across 4 substates	9.92	38.99	18.74	20.35
Relative Absolute Bias	2.25	1.22	0.72	0.11
OH (design-based)	9.97	41.73	20.32	22.04
OH1	9.86	42.08	19.89	21.74
OH2	11.03	42.39	19.08	21.28
OH3	10.31	40.68	20.32	21.93
OH4	10.48	41.52	20.50	22.20
Average across 4 substates	10.42	41.67	19.95	21.79
Relative Absolute Bias	4.48	0.15	1.84	1.13
PA (design-based)	9.30	42.13	20.55	21.97
PA1	11.17	44.23	20.02	21.99
PA2	9.94	39.78	19.15	20.66
PA3	10.03	42.50	20.54	22.08
PA4	9.64	41.15	18.97	20.65
Average across 4 substates	10.20	41.92	19.67	21.35
Relative Absolute Bias	9.67	0.50	4.26	2.84
TX (design-based)	11.07	35.62	20.08	21.31
TX1	10.66	34.17	19.50	20.62
TX2	10.31	40.01	20.94	22.50
TX3	11.64	32.77	19.33	20.40
TX4	10.53	37.29	20.84	22.04
Average across 4 substates	10.78	36.06	20.15	21.39
Relative Absolute Bias	2.59	1.24	0.35	0.39
Average Relative Absolute Bias	4.41	1.02	1.56	0.98

Note: Relative Absolute Bias = 100 × abs(Average SAE over 4 substates - Large State design-based estimate) / Large State design-based estimate.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.25 Relative Absolute Bias for Past Month Use of Cigarettes Based on Pooled 1999 and 2000 Data

State	Age in Years			Total
	12-17	18-25	26+
CA (design-based)	8.73	29.62	22.07	21.62
CA1	9.53	30.29	22.31	21.99
CA2	8.96	32.22	21.72	21.74
CA3	9.30	30.84	21.28	21.25
CA4	8.87	29.25	20.82	20.65
Average across 4 substates	9.16	30.65	21.53	21.41
Relative Absolute Bias	4.93	3.49	2.41	0.98
FL (design-based)	10.92	34.60	25.16	24.85
FL1	10.67	35.75	24.02	24.04
FL2	12.75	34.25	25.95	25.62
FL3	10.10	35.28	25.34	24.99
FL4	12.85	36.80	24.37	24.63
Average across 4 substates	11.59	35.52	24.92	24.82
Relative Absolute Bias	6.16	2.65	0.96	0.13
IL (design-based)	15.61	43.44	25.57	26.93
IL1	13.45	41.65	24.49	25.64
IL2	16.27	44.36	27.65	28.70
IL3	16.16	42.55	24.36	25.94
IL4	14.76	40.70	24.66	25.78
Average across 4 substates	15.16	42.31	25.29	26.51
Relative Absolute Bias	2.87	2.60	1.11	1.53
MI (design-based)	15.68	43.81	25.14	26.57
MI1	16.08	44.79	25.40	26.94
MI2	16.06	42.04	26.92	27.74
MI3	14.70	42.18	26.85	27.57
MI4	16.79	42.27	26.36	27.42
Average across 4 substates	15.91	42.82	26.38	27.42
Relative Absolute Bias	1.45	2.27	4.93	3.17
NY (design-based)	12.28	36.29	23.95	24.31
NY1	12.89	37.88	25.07	25.44
NY2	12.52	35.60	23.19	23.65
NY3	11.36	33.66	23.54	23.58
NY4	11.98	38.06	24.53	24.94
Average across 4 substates	12.19	36.30	24.08	24.40
Relative Absolute Bias	0.76	0.03	0.54	0.38
OH (design-based)	15.83	45.66	28.21	29.21
OH1	16.20	44.45	26.39	27.69
OH2	14.48	43.82	26.18	27.27
OH3	17.37	47.51	29.15	30.32
OH4	16.18	42.92	29.07	29.54
Average across 4 substates	16.06	44.67	27.70	28.71
Relative Absolute Bias	1.45	2.16	1.83	1.71
PA (design-based)	16.21	42.32	24.97	26.14
PA1	16.94	39.47	23.81	24.97
PA2	17.27	42.45	26.64	27.57
PA3	14.71	40.80	24.96	25.81
PA4	16.54	44.22	25.88	27.11
Average across 4 substates	16.36	41.74	25.32	26.37
Relative Absolute Bias	0.97	1.39	1.44	0.87
TX (design-based)	12.73	34.49	23.12	23.57
TX1	13.11	35.49	23.15	23.78
TX2	11.83	36.65	23.12	23.78
TX3	12.43	32.79	22.03	22.48
TX4	12.17	35.52	25.17	25.17
Average across 4 substates	12.39	35.11	23.37	23.80
Relative Absolute Bias	2.74	1.79	1.07	0.98
Average Relative Absolute Bias	2.67	2.05	1.79	1.22

Note: Relative Absolute Bias = 100 × abs(Average SAE over 4 substates - Large State design-based estimate) / Large State design-based estimate.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999 and 2000.

Table B.26 Ratio of Average Widths for Pooled 1999 and 2000 Data

State	Age in Years			Total
	12-17	18-25	26+
Past Month Use of Marijuana
CA	0.76	0.71	0.75	0.76
FL	0.72	0.76	0.77	0.81
IL	0.62	0.70	0.79	0.74
MI	0.72	0.81	0.73	0.80
NY	0.79	0.70	0.91	0.85
OH	0.67	0.64	0.62	0.67
PA	0.71	0.65	0.65	0.71
TX	0.72	0.72	0.67	0.75
Average	0.71	0.71	0.74	0.76
Past Year Use of Cocaine
CA	0.70	0.66	0.52	0.58
FL	0.53	0.60	0.60	0.64
IL	0.65	0.66	0.46	0.54
MI	0.54	0.58	0.59	0.65
NY	0.46	0.71	0.75	0.79
OH	0.60	0.62	0.61	0.68
PA	0.61	0.59	0.50	0.57
TX	0.62	0.65	0.72	0.71
Average	0.59	0.63	0.59	0.65
Past Month "Binge" Alcohol Use
CA	0.82	0.76	0.77	0.81
FL	0.71	0.63	0.72	0.73
IL	0.64	0.66	0.70	0.69
MI	0.69	0.75	0.71	0.71
NY	0.74	0.60	0.76	0.77
OH	0.85	0.60	0.75	0.72
PA	0.75	0.59	0.70	0.69
TX	0.79	0.71	0.70	0.72
Average	0.75	0.66	0.73	0.73
Past Month Use of Cigarettes
CA	0.82	0.84	0.65	0.66
FL	0.71	0.74	0.86	0.86
IL	0.67	0.83	0.69	0.69
MI	0.79	0.71	0.73	0.72
NY	0.64	0.76	0.82	0.82
OH	0.72	0.81	0.75	0.75
PA	0.72	0.69	0.81	0.78
TX	0.72	0.74	0.68	0.66
Average	0.72	0.77	0.75	0.74

Note: Ratio = Average width of model-based PIs for substates / Average width of design-based CIs for substates.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

Table B.27 1999 NHSDA Weighted Screening and Interview Response Rates, by State

State	Screening Response Rate	Interview Response Rate	Overall Response Rate	State	Screening Response Rate	Interview Response Rate	Overall Response Rate
Total	89.63	68.55	61.44	Missouri	91.32	73.59	67.21
Alabama	92.60	71.36	66.08	Montana	92.76	76.39	70.86
Alaska	91.07	77.20	70.31	Nebraska	89.99	72.05	64.84
Arizona	94.43	65.87	62.21	Nevada	79.89	63.05	50.37
Arkansas	95.71	80.45	77.00	New Hampshire	85.36	69.87	59.65
California	87.47	64.12	56.08	New Jersey	89.65	65.24	58.48
Colorado	91.62	65.84	60.32	New Mexico	96.12	77.77	74.75
Connecticut	85.62	58.60	50.17	New York	84.28	59.98	50.55
Delaware	87.13	58.36	50.85	North Carolina	92.87	71.84	66.72
District of Columbia	93.35	79.93	74.61	North Dakota	89.89	77.48	69.65
Florida	89.94	68.20	61.33	Ohio	90.35	67.78	61.24
Georgia	90.47	66.97	60.59	Oklahoma	91.58	67.79	62.08
Hawaii	89.11	67.61	60.25	Oregon	85.20	71.57	60.98
Idaho	92.93	75.45	70.11	Pennsylvania	92.34	68.99	63.71
Illinois	87.35	63.74	55.68	Rhode Island	86.68	66.72	57.83
Indiana	91.68	73.06	66.98	South Carolina	91.96	65.92	60.61
Iowa	92.44	69.69	64.41	South Dakota	94.35	76.14	71.84
Kansas	90.59	72.89	66.03	Tennessee	90.92	67.70	61.56
Kentucky	92.36	73.75	68.12	Texas	92.57	75.12	69.54
Louisiana	94.81	76.97	72.98	Utah	93.16	81.70	76.11
Maine	89.96	75.18	67.63	Vermont	90.26	74.49	67.24
Maryland	87.78	64.66	56.76	Virginia	89.84	66.28	59.55
Massachusetts	80.59	61.82	49.82	Washington	86.49	75.06	64.92
Michigan	88.21	66.54	58.70	West Virginia	95.59	74.31	71.03
Minnesota	89.46	77.72	69.53	Wisconsin	90.19	73.05	65.89
Mississippi	94.51	82.77	78.23	Wyoming	93.79	72.62	68.11

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 1999.

Table B.28 2000 NHSDA Weighted Screening and Interview Response Rates, by State

State	Screening Response Rate	Interview Response Rate	Overall Response Rate	State	Screening Response Rate	Interview Response Rate	Overall Response Rate
Total	92.84	73.93	68.64	Missouri	92.25	70.80	65.31
Alabama	95.50	77.98	74.47	Montana	94.91	80.21	76.13
Alaska	95.43	80.24	76.58	Nebraska	93.13	74.58	69.46
Arizona	92.99	73.78	68.61	Nevada	92.08	74.44	68.54
Arkansas	97.19	81.00	78.73	New Hampshire	92.41	75.12	69.42
California	90.99	69.50	63.24	New Jersey	91.96	66.56	61.21
Colorado	94.84	75.26	71.37	New Mexico	97.43	80.80	78.72
Connecticut	89.83	71.36	64.10	New York	88.78	73.73	65.46
Delaware	92.91	68.25	63.42	North Carolina	94.51	73.19	69.17
District of Columbia	93.50	85.56	80.00	North Dakota	94.43	79.46	75.03
Florida	94.64	75.73	71.67	Ohio	94.89	75.79	71.92
Georgia	92.95	69.76	64.84	Oklahoma	93.06	74.85	69.66
Hawaii	91.95	78.45	72.14	Oregon	91.87	73.91	67.90
Idaho	93.94	74.45	69.94	Pennsylvania	94.37	73.50	69.36
Illinois	88.71	65.59	58.19	Rhode Island	91.26	74.11	67.63
Indiana	92.62	73.87	68.42	South Carolina	94.69	77.84	73.71
Iowa	94.78	80.00	75.83	South Dakota	95.15	76.67	72.95
Kansas	92.28	73.45	67.79	Tennessee	90.25	72.45	65.39
Kentucky	95.79	84.14	80.59	Texas	94.72	78.12	74.00
Louisiana	95.04	80.81	76.80	Utah	95.11	83.44	79.36
Maine	92.39	78.46	72.49	Vermont	92.62	80.80	74.83
Maryland	94.88	76.88	72.94	Virginia	91.44	75.18	68.75
Massachusetts	89.77	66.45	59.65	Washington	93.59	75.45	70.61
Michigan	93.19	73.18	68.20	West Virginia	95.19	78.17	74.41
Minnesota	94.66	80.62	76.32	Wisconsin	94.33	75.06	70.81
Mississippi	93.60	79.14	74.07	Wyoming	95.41	76.61	73.09

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

¹ The eight large sample States are California, Florida, Illinois, Michigan, New York, Ohio, Pennsylvania, and Texas.

² The panel included William Bell of the U.S. Bureau of the Census; Partha Lahiri of the University of Nebraska; Balgobin Nandram of Worcester Polytechnic Institute and the National Center for Health Statistics; Wesley Schaible, formerly Associate Commissioner for Research and Evaluation at the Bureau of Labor Statistics; J.N.K. Rao of Carleton University; and Alan Zaslavsky of Harvard University. Other attendees involved in the development or discussion were Ralph Folsom, Judith Lessler, Avinash Singh, and Akhil Vaish of RTI and Joe Gfroerer and Doug Wright of SAMHSA.

This page was last updated on December 30, 2008.

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