append_KenRCATs

Append KenRCATs Results with Input Parameters

internal

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.

Mackson Ncube

mmiCATs

Cluster Adjusted t Statistic Applications

mightymetrika, LLC 

append_KenRCATs function

<dl><dt>df</dt>
<dd>A data frame containing simulation results.</dd>
<dt>input</dt>
<dd>A list of input parameters from the Shiny app.</dd></dl>

Arguments

Append KenRCATs Results with Input Parameters — append_KenRCATs

<dl>

<dt>df</dt>
<dd>A data frame containing simulation results.</dd>


<dt>input</dt>
<dd>A list of input parameters from the Shiny app.</dd>

</dl>

append_KenRCATs: Append KenRCATs Results with Input Parameters

Description

Usage

Value

Arguments