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mmiCATs
View on CRAN: Click
here
Download and install mmiCATs package within the R console
Install from CRAN:
install.packages("mmiCATs")
Install from Github:
library("remotes")
install_github("cran/mmiCATs")
Install by package version:
library("remotes")
install_version("mmiCATs", "0.2.0")
Attach the package and use:
library("mmiCATs")
Maintained by
Mackson Ncube
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.mmiCATs . https://github.com/mightymetrika/mmiCATs/issues . https://github.com/mightymetrika/mmiCATs . mmiCATs results . mmiCATs.pdf . mmiCATs_0.2.0.tar.gz . mmiCATs_0.2.0.zip . mmiCATs_0.2.0.zip . mmiCATs_0.2.0.zip . mmiCATs_0.2.0.tgz . mmiCATs_0.2.0.tgz . mmiCATs_0.2.0.tgz . mmiCATs_0.2.0.tgz . mmiCATs_0.2.0.tgz . mmiCATs_0.2.0.tgz . mmiCATs archive . https://CRAN.R-project.org/package=mmiCATs .
First Published: 2024-02-16
Latest Update: 2024-02-21
Description:
Simulation results detailed in Esarey and Menger (2019)
demonstrate that cluster adjusted t statistics (CATs) are an effective method
for correcting standard errors in scenarios with a small number of clusters.
The 'mmiCATs' package offers a suite of tools for working with CATs. The
mmiCATs() function initiates a 'shiny' web application, facilitating
the analysis of data utilizing CATs, as implemented in the cluster.im.glm()
function from the 'clusterSEs' package. Additionally, the pwr_func_lmer()
function is designed to simplify the process of conducting simulations to
compare mixed effects models with CATs models. For educational purposes, the
CloseCATs() function launches a 'shiny' application card game, aimed at enhancing
users' understanding of the conditions under which CATs should be preferred
over random intercept models.
How to cite:
Mackson Ncube (2024). mmiCATs: Cluster Adjusted t Statistic Applications. R package version 0.2.0, https://cran.r-project.org/web/packages/mmiCATs. Accessed 10 Mar. 2025.
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