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National Center for Health Statistics  Monitoring the Nation's Health

NHANES III Web Tutorial

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Clean & Recode Data

Purpose

Cleaning and recoding NHANES III data is necessary before you can use NHANES III variables for your analyses. NHANES III data may need to be cleaned if there are missing data, skip patterns, or outliers in the dataset. Alternatively, you may need to recode data in order to define new variable values.

 

Task 1: Identify, Recode, and Evaluate Missing Data

Missing values may distort your analysis results. You must evaluate the extent of missing data in your dataset to determine whether the data are useable without additional re-weighting for item non-response.

 

Task 2: Check for Skip Patterns and Explain How They Affect Results

The significance of a skip pattern depends on the question leading to the skip pattern, the questions within that skip pattern, and the variables you intend to analyze.

warning icon If you fail to check for skip patterns, you may obtain only a proportion of the population, instead of the entire study population.

 

Task 3: Check Distributions and Describe the Impact of Influential Outliers

Before you analyze your data, it is very important that you check the distribution and normality of the data and identify outliers for continuous variables.

 

Task 4: Recode Variables

Recoding is an important step for preparing an analytical dataset. You may want to recode variables to create new variables that fit your analytic needs.

 

Page Last Modified: March 25, 2008

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

 

Safer Healthier People

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