geeCRT
Bias-Corrected GEE for Cluster Randomized Trials
Population-averaged models have been increasingly used in the design and analysis of cluster randomized trials (CRTs). To facilitate the applications of population-averaged models in CRTs, the package implements the generalized estimating equations (GEE) and matrix-adjusted estimating equations (MAEE) approaches to jointly estimate the marginal mean models correlation models both for general CRTs and stepped wedge CRTs. Despite the general GEE/MAEE approach, the package also implements a fast cluster-period GEE method by Li et al. (2022) doi:10.1093/biostatistics/kxaa056 specifically for stepped wedge CRTs with large and variable cluster-period sizes and gives a simple and efficient estimating equations approach based on the cluster-period means to estimate the intervention effects as well as correlation parameters. In addition, the package also provides functions for generating correlated binary data with specific mean vector and correlation matrix based on the multivariate probit method in Emrich and Piedmonte (1991) doi:10.1080/00031305.1991.10475828 or the conditional linear family method in Qaqish (2003) doi:10.1093/biomet/90.2.455.
- Version1.1.3
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release02/19/2024
Documentation
Team
Hengshi Yu
Fan Li
Show author detailsRolesAuthorElizabeth L. Turner
Show author detailsRolesAuthorPaul Rathouz
Show author detailsRolesAuthorJohn Preisser
Show author detailsRolesAuthor
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- Imports3 packages
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