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Simulation results detailed in Esarey and Menger (2019) <doi:10.1017/psrm.2017.42> 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.
Version: | 0.2.0 |
Imports: | broom, broom.mixed, clusterSEs, DT, lmerTest, MASS, mmcards, pool, robust, robustbase, RPostgres, shiny, shinythemes |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2024-08-26 |
DOI: | 10.32614/CRAN.package.mmiCATs |
Author: | Mackson Ncube [aut, cre], mightymetrika, LLC [cph, fnd] |
Maintainer: | Mackson Ncube <macksonncube.stats at gmail.com> |
BugReports: | https://github.com/mightymetrika/mmiCATs/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/mightymetrika/mmiCATs |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | mmiCATs results |
Reference manual: | mmiCATs.pdf |
Package source: | mmiCATs_0.2.0.tar.gz |
Windows binaries: | r-devel: mmiCATs_0.2.0.zip, r-release: mmiCATs_0.2.0.zip, r-oldrel: mmiCATs_0.2.0.zip |
macOS binaries: | r-release (arm64): mmiCATs_0.2.0.tgz, r-oldrel (arm64): mmiCATs_0.2.0.tgz, r-release (x86_64): mmiCATs_0.2.0.tgz, r-oldrel (x86_64): mmiCATs_0.2.0.tgz |
Old sources: | mmiCATs archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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