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Tools for Selecting Working Correlation Structures When Using Weighted GEE to Model Longitudinal Survey Data.

Philip M Westgate1, Brady T West2

  • 1Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY 40536, U.S.A.

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|April 6, 2023
PubMed
Summary
This summary is machine-generated.

Weighted generalized estimating equations (GEE) improve longitudinal survey data analysis. This study extends correlation selection criteria for weighted GEE, offering an R function to enhance parameter estimation and reduce standard errors in survey data.

Keywords:
Complex Sample Survey DataCorrelation Structure SelectionGeneralized Estimating EquationsLongitudinal Survey DataWeighted Estimation

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Area of Science:

  • Statistics
  • Biostatistics
  • Survey Methodology

Background:

  • Weighted generalized estimating equations (GEE) are widely used for marginal analysis of longitudinal survey data.
  • GEE provides consistent estimates if population mean and weights are correct, but correlation structure accuracy can improve results.
  • Selecting an appropriate working correlation structure is crucial for efficient parameter estimation in GEE.

Purpose of the Study:

  • To extend correlation selection criteria for weighted GEE in longitudinal survey data analysis.
  • To provide a practical R function for implementing these extended criteria.
  • To discuss correlation selection strategies within existing software limitations.

Main Methods:

  • Extension of existing correlation selection criteria for weighted GEE.
  • Development and demonstration of a novel R function for correlation selection.
  • Application of methods to real-world longitudinal survey data on elderly falls.

Main Results:

  • Demonstration of how correlation selection criteria can be effectively adapted for weighted GEE.
  • Successful implementation of an R function facilitating improved analysis.
  • Insights into correlation selection for analyses using standard software.

Conclusions:

  • The proposed methods enhance the analysis of longitudinal survey data using weighted GEE.
  • The R function provides a valuable tool for researchers.
  • Accurate correlation structure modeling is beneficial for parameter estimation in weighted GEE analyses.