An official website of the United States government
United States Department of Labor
United States Department of Labor
The .gov means it's official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information,
make sure you're on a federal government site.
The site is secure.
The
https:// ensures that you are connecting to the official website and that any
information you provide is encrypted and transmitted securely.
Office of Survey Methods Research
SHARE ON:
More Information
Published Year: 2024
Survey/Program(s): National Health and Nutrition Examination Survey
Catalog: Statistical Survey Paper
Download PDF
Bayesian Inference for Repeated Measures Under Informative Sampling
Abstract
Survey data are often randomly drawn from an underlying population of inferential interest under a multistage, complex sampling design. A sampling weight proportional to the number of individuals in the population that each sampled individual represents is released. The sampling design is informative with respect to a response variable of interest if the variable correlates with the sampling weights. The distribution for the variables of interest differs in the sample and in the population, requiring correction to the sample distribution to approximate the population. We focus on model-based Bayesian inference for repeated (continuous) measures associated with each sampled individual. We devise a model for the joint estimation of response variable(s) of interest and sampling weights to account for the informative sampling design in a formulation that captures the association of the measures taken on the same individual incorporating individual specific random-effects. We show that our approach yields correct population inference on the observed sample of units and compare its performance with competing method via simulation. Methods are compared using bias, mean square error, coverage, and length of credible intervals. We demonstrate our approach using a National Health and Nutrition Examination Survey dietary dataset modeling daily protein consumption.