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  "Package": "mmiCATs",
  "Title": "Cluster Adjusted t Statistic Applications",
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  "Authors@R": "c(\nperson(\"Mackson\", \"Ncube\", , \"macksonncube.stats@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"mightymetrika, LLC\", role = c(\"cph\", \"fnd\"))\n)",
  "Description": "Simulation results detailed in Esarey and Menger (2019)\n<doi:10.1017/psrm.2017.42> demonstrate that cluster adjusted t\nstatistics (CATs) are an effective method for correcting\nstandard errors in scenarios with a small number of clusters.\nThe 'mmiCATs' package offers a suite of tools for working with\nCATs. The mmiCATs() function initiates a 'shiny' web\napplication, facilitating the analysis of data utilizing CATs,\nas implemented in the cluster.im.glm() function from the\n'clusterSEs' package. Additionally, the pwr_func_lmer()\nfunction is designed to simplify the process of conducting\nsimulations to compare mixed effects models with CATs models.\nFor educational purposes, the CloseCATs() function launches a\n'shiny' application card game, aimed at enhancing users'\nunderstanding of the conditions under which CATs should be\npreferred over random intercept models.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
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  "Repository": "https://mightymetrika.r-universe.dev",
  "Date/Publication": "2024-09-03 15:39:53 UTC",
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  "_published": "2026-05-22T19:15:20.351Z",
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