Sample Code & Datasets

Below is a listing of all the sample code and datasets used in the NHANES I tutorial. They are organized by module and then task. If a module or task is not listed it is because it did not have a related program. All programs are SAS programs (i.e. SAS Survey Procedures or SAS-callable SUDAAN) and the datasets are SAS datasets for Windows.

Program code used in this tutorial follow procedures available in SAS 9.1 or SAS 8.0 and SUDAAN 9.0 or SUDAAN 8.0.

These programs use variable formats listed in the Tutorial Formats page. You may need to format the variables in your dataset the same way to reproduce results presented in the tutorial.

A regular left-click may not download the SAS datasets or SAS code correctly. Your browser may try to open and attempt to interpret the contents of the dataset or program. If this happens, right-click the link and save the dataset or program to your hard drive. After it  has downloaded, the use your statistical software program to open the dataset to view it.

Download Data Files

• Task 3: How to Run the SAS Code to Create the SAS Data Files in a Permanent Library
• Program to Modify Filenames and Assign Filenames

Keep & Merge Datasets

• Task 1: How to Keep NHANES I Data
  • Program to keep NHANES I data
  • Adult History Dataset
  • Anthropometry Dataset
  • Biochemistry Dataset
  • Examination Dataset
  • General Medical Dataset
     
• Task 2: How to Merge NHANES I Data
  •  Program to merge NHANES I data
  • Output of Program to merge NHANES I data and check results
  • Adult History Dataset
  • Anthropometry Dataset
  • Biochemistry Dataset
  • Examination Dataset
  • General Medical Dataset

Clean & Recode Data

• Task 1: Identify, Recode, and Evaluate Missing Data
  
  • Step 1 Identify missing and unavailable values
    • Program to check for missing values
    • Output of program to check for missing values
    • Dataset
  • Step 2 Recode unavailable values as missing
    • Program to assign missing values one variable at a time
    • Program to assign missing values by group using an array
    • Dataset
  • Step 3 Evaluate extent of missing data
    • Program to check the extent of missing data
    • Output of Program to check extent of missing data
    • Dataset with missing data recoded

   

• Task 3: Check Distributions and Describe the Impact of Influential Outliers
  • Step 1 Check distributions by running a univariate analysis
    • Program to Plot Distribution of Continuous Variable
    • Output of program to plot distribution of continuous variables
    • Dataset
  • Step 2 Plot a graph of survey weight against the distribution of the variable
    • Program to Plot Exam Weight Against Cholesterol
    • Output of program to plot exam weight against cholesterol
    • Dataset
  • Step 3 Identify outliers and compare estimates with outliers deleted against the original estimates with outliers included
    • Program to Create Dataset Without Outliers and Output Means of Both Datasets
    • Output of means of both datasets with and without outliers
    • Dataset with outliers
    • Dataset without outliers
    
     
• Task 4: Recode Variables
  • Step 1 Recode based on alternate definitions
    • Program to Recode as Necessary Based on Alternate Definitions
    • Dataset
  • Step 2 Check recodes
    • Program to Check Recodes using Cross Tabulations or proc means
    • Output of program to check recodes using cross tabulations or proc means
    • Dataset

NHANES I Tutorial Home

Survey Orientation

Preparing an Analytic Dataset

Survey Design Factors

Additional Resources

National Center for Health Statistics
3311 Toledo Road
Hyattsville, MD 20782
Phone: 1-866-441-NCHS (6247)
For data inquiries, use
nchsquery@cdc.gov

Problems or comments about the Tutorial?
Email the Tutorial Team: NHANESWebTutorial@cdc.gov

Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA 30333, U.S.A
Tel: (404) 639-3311 / Public Inquiries: (404) 639-3534 / (800) 311-3435