CRAN/E | geeCRT

geeCRT

Bias-Corrected GEE for Cluster Randomized Trials

Installation

About

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.

Key Metrics

Version 1.1.3
R ≥ 3.6.0
Published 2024-02-19 75 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks geeCRT results

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Maintainer

Maintainer

Hengshi Yu

hengshi@umich.edu

Authors

Hengshi Yu

aut / cre

Fan Li

aut

Paul Rathouz

aut

Elizabeth L. Turner

aut

John Preisser

aut

Material

NEWS
Reference manual
Package source

Vignettes

geeCRT package for the design and analysis of cluster randomized trials

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

geeCRT archive

Depends

R ≥ 3.6.0

Imports

MASS
rootSolve
mvtnorm

Suggests

knitr
rmarkdown