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Sample Design

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NHANES uses a complex, multistage, probability sampling design. Researchers need to take this into account in their analyses by appropriately specifying the sampling design parameters.

This can be done using any statistical software that can analyze complex survey designs. Specifying sampling design parameters using SUDAAN and SAS Survey procedures is presented in this module.


Overview: NHANES Sample Design

NHANES data are not obtained using a simple random sample. Rather, a complex, multistage, probability sampling design is used to select participants representative of the civilian, non-institutionalized US population. Oversampling of certain population subgroups is done to increase the reliability and precision of health status indicator estimates for these groups.



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.




Task 1: Specify Sampling Parameters in NHANES Using SUDAAN or SAS Survey Procedures

SUDAAN and SAS Survey are statistical software packages that can be used to analyze complex survey data such as NHANES.


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