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geeCRT  

Bias-Corrected GEE for Cluster Randomized Trials
View on CRAN: Click here


Download and install geeCRT package within the R console
Install from CRAN:
install.packages("geeCRT")

Install from Github:
library("remotes")
install_github("cran/geeCRT")

Install by package version:
library("remotes")
install_version("geeCRT", "1.1.3")



Attach the package and use:
library("geeCRT")
Maintained by
Hengshi Yu
[Scholar Profile | Author Map]
First Published: 2020-11-11
Latest Update: 2023-03-08
Description:
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) 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) or the conditional linear family method in Qaqish (2003) .
How to cite:
Hengshi Yu (2020). geeCRT: Bias-Corrected GEE for Cluster Randomized Trials. R package version 1.1.3, https://cran.r-project.org/web/packages/geeCRT. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.0.1 (2020-11-11 16:50), 0.1.0 (2021-04-15 09:10), 0.1.1 (2021-10-10 06:10), 1.1.0 (2023-03-08 09:50), 1.1.1 (2023-09-17 02:10), 1.1.2 (2023-10-23 05:40)
Other packages that cited geeCRT R package
View geeCRT citation profile
Other R packages that geeCRT depends, imports, suggests or enhances
Complete documentation for geeCRT
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