 |
|
NCES: 92007 February 1992 |
PDF & Related InfoA stratified sample of 890 schools was drawn from the 1988-89 list of public schools compiled by the National Center for Education Statistics (NCES). This file contains about 85,000 listings and is part of the NCES Common Core of Data (CCD) School Universe. Regular, vocational education, and alternative schools in the 50 states and District of Columbia were included in the survey universe, while special education schools were excluded from the frame prior to sampling. Schools not operated by local education agencies and those including only prekindergarten or kindergarten were also excluded. With these exclusions, the final sampling frame consisted of approximately 81,100 eligible schools. The schools were stratified by type of locale (city, urban fringe, town, rural) and level of instruction (elementary, secondary, and combined schools). Within each of the 12 strata, schools were sorted first by state, then district (within each state), and then enrollment size (within each district). Next schools were selected with probabilities proportionate to the square root of the number of full-time-equivalent (FTE) teachers in the school.
In mid-April 1991, questionnaires (see Appendix B) were mailed to the 890 principals in the sample. Six of the schools were found to be out-of-scope, leaving 884 principals in the sample. Telephone followup of nonrespondents was initiated in mid-May; data collection was completed by the end of June. For the eligible principals that received surveys, a response rate of 94 percent (830 responding principals divided by the 884 principals in the sample) was obtained (see Table B). Item nonresponse ranged from 0.0 percent to 3.1 percent.
The response data were weighted to produce national estimates. The weights were designed to adjust for the variable probabilities of selection and differential nonresponse. The findings in this report are estimates based on the sample selected and, consequently, are subject to sampling variability.
To minimize the potential for nonsampling errors, the questionnaire was pretested with principals like those who completed the survey. During the design of the survey and the survey pretest, an effort was made to check for consistency of interpretation of questions and to eliminate ambiguous items. The questionnaire and instructions were extensively reviewed by the National Center for Education Statistics, as well as the Office of Educational Research and Improvement, the Office of the Undersecretary, and the Drug Planning and Outreach Staff, Office of Elementary/Secondary Education, in the Department of Education. Manual and machine editing of the questionnaires were conducted to check the data for accuracy and consistency. Cases with missing or inconsistent items were recontacted by telephone. Imputations for item nonresponse were not implemented, as item nonresponse rates were less than 5 percent (for most items, nonresponse rates were less than 1 percent). Data were keyed with 100 percent verification.
The standard error is a measure of the variability of estimates due to sampling. It indicates the variability of a sample estimate that would be obtained from all possible samples of a given design and size. Standard errors can be used as a measure of the precision expected from a particular sample. If all possible samples were surveyed under similar conditions, intervals of 1.96 standard errors below to 1.96 standard errors above a particular statistic would include the true population parameter being estimated in about 95 percent of the samples. This is a 95 percent confidence interval. For example, the estimated percentage of principals who consider student alcohol use a serious or moderate problem in their school is 11 percent, and the estimated standard error is 1.0 percent. The 95 percent confidence interval for the statistic extends from 11- (1.0 times 1.96) to 11 + (1.0 times 1.96), or from 9 to 13 percent.
Estimates of standard errors were computed using a technique known as jackknife replication. As with any replication method, jackknife replication involves constructing a number of subsamples (replicates) from the full sample and computing the statistic of interest for each replicate. The mean square error of the replicate estimates around the full sample estimate provides an estimate of the variance of the statistic (e.g., Wolter, 1985, Chapter 4). To construct the replications, 30 stratified subsamples of the full sample were created and then dropped one at a time to define 30 jackknife replicates (e.g., Wolter, 1985, page 183). A proprietary computer program (WESVAR), available at Westat, Inc., was used to calculate the estimates of standard errors. The software runs under IBM/OS and VAX/VMS systems.
The survey was performed under contract with Westat, Inc., using the Fast Response Survey System (FRSS). Westat's Project Director was Elizabeth Farris, and the Survey Manager was Wendy Mansfield. Judi Carpenter was the NCES Project Officer. The data requestor was Mary Frase, Data Development Division, NCES; outside consultants were Oliver Moles, Office of Research, Office of Educational Research and Improvement (OERI), and Kimmon Richards, Planning and Evaluation Service, the Office of the Undersecretary.
The report was reviewed by Anthony Adams, OERI Fellow, Assistant Professor of Sociology, Eastern Michigan University; Wendy Bruno, Statistician, Bureau of the Census; James Keefe, Director of Research, National Association of Secondary School Principals; Oliver Moles, Office of Research, OERI; and Kimmon Richards, Planning and Evaluation Service, the Office of the Undersecretary. Within NCES, report reviewers were Macknight Black, PostSecondary Education Statistics Division, and Edie MacArthur, Data Development Division.
For more information about the Fast Response Survey System or the Surveys on Safe, Disciplined, Drug-Free Schools, contact Judi Carpenter, Office of Educational Research and Improvement, National Center for Education Statistics, 555 New Jersey Avenue NW, Washington, DC 20208-5651, telephone (202) 219-1333.
The WESVAR Procedures, 1989. Rockville, MD: Westat, Inc.
Wolter, K. 1985. Introduction to Variance Estimation. Springer-Verlag.
){kind=link}