Multiply robust generalized estimating equations for cluster randomized trials with missing outcomes
Year: 2024
Type: article
Abstract: Generalized estimating equations (GEEs) provide a useful framework for estimating marginal regression parameters based on data from cluster randomized trials (CRTs), but they can result in inaccurate parameter estimates when some outcomes are informatively missing. Existing techniques to handle missing outcomes in CRTs rely on correct specification of a propensity score model, a covariate-conditional mean outcome model, or require at least one of these two models to be correct, which can be challenging in practice. In this article, we develop new weighted GEEs to simultaneously estimate the marginal mean, scale, and correlation parameters in CRTs with missing outcomes, allowing for multiple propensity score models and multiple covariate-conditional mean models to be specified. The resulting estimators are consistent provided that any one of these models is correct. An iterative algorithm is provided for implementing this more robust estimator and practical considerations for specifying multiple models are discussed. We evaluate the performance of the proposed method through Monte Carlo simulations and apply the proposed multiply robust estimator to analyze the Botswana Combination Prevention Project, a large HIV prevention CRT designed to evaluate whether a combination of HIV-prevention measures can reduce HIV incidence.
Source: Statistics in Medicine
DOI: 10.1002/sim.10027
Authors: Dustin J. Rabideau, Fan Li, Rui Wang
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: bronze
Awards: G166798358, IMPACT EVALUATION OF COMBINATION HIV PREVENTION INTERVENTIONS IN BOTSWANA, Network modeling and robust estimation of the intraclass correlation coefficient to inform the design and analysis of cluster randomized trials for infectious diseases, G6582859664, GH16-002, BOTSWANA: IMPACT EVALUATION OF COMBINATION HIV PREVENTION INTERVENTIONS, Biostatistics/Epidemiology Training Grants in AIDS
OpenAlex ID: W4391608502