Overview of NHANES Survey Design and Weighting
NHANES uses a complex sampling design and constructs sample weights to produce nationally representative data. Learning about the features of the NHANES survey design and weighting will help ensure that the results of your physical activity analyses represent unbiased estimates with accurate statistical significance levels.
Task 1: Explain NHANES Survey Design
NHANES data are obtained through a complex, multistage, probability sampling design that selects participants who are representative of the civilian, non-institutionalized US population. Participants are not selected by a simple random sample. Oversampling of certain population subgroups is done to increase the reliability and precision of health status indicator estimates for those groups.
Task 2: Explain NHANES Sample Weights
NHANES has constructed various sample weights for single 2-year survey cycles to take into account survey non-response, oversampling, post-stratification, and sampling error. This task describes how sample weights are constructed in NHANES. Due to the way NHANES participants are selected, sample weights always must be used to produce an unbiased national estimate.
For NHANES datasets, the use of sampling weights and sample design variables is recommended for all analyses because the sample design is a clustered design and incorporates differential probabilities of selection. If you fail to account for the sampling parameters, you may obtain biased estimates and overstate significance levels.