Cluster Adjusted t Statistic Applications R package mmiCATs version 0.2.0 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. Software Imports: broom, broom.mixed, clusterSEs, DT, lmerTest, MASS, mmcards, pool, robust, robustbase, RPostgres, shiny, shinythemes Suggests: testthat (>= 3.0.0) Mackson Ncube <macksonncube.stats@gmail.com> Comprehensive R Archive Network (CRAN) Mackson Ncube [aut, cre], mightymetrika, LLC [cph, fnd] MIT + file LICENSE (https://CRAN.R-project.org/package=mmiCATs/LICENSE) 2024-08-26 application/tgz https://CRAN.R-project.org/package=mmiCATs doi:10.32614/CRAN.package.mmiCATs