Statistics, Department of

The R Journal
Date of this Version
12-2017
Document Type
Article
Citation
The R Journal (December 2017) 9(2); Editor: Roger Bivand
Abstract
Semi-parametric approaches based on generalized estimating equations (GEE) are widely used to analyze correlated outcomes in longitudinal settings. In this paper, we present a package CRTgeeDR developed for cluster randomized trials with missing data (CRTs). For use of inverse probability weighting to adjust for missing data in cluster randomized trials, we show that other software lead to biased estimation for non-independence working correlation structure. CRTgeeDR solves this problem. We also extend the ability of existing packages to allow augmented Doubly Robust GEEestimation (DR). Simulation studies demonstrate the consistency of estimators implemented in CRTgeeDR compared to packages such as geepack and the gains associated with the use of the DR for analyzing a binary outcome using a logistic regression. Finally, we illustrate the method on data from a sanitation CRT in developing countries.
Included in
Numerical Analysis and Scientific Computing Commons, Programming Languages and Compilers Commons
Comments
Copyright 2017, The R Foundation. Open access material. License: CC BY 4.0