parse_list_input

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 

parse_list_input function

<dl><dt>input_string</dt>
<dd>A string representation of a list.</dd></dl>

Arguments

Parse String Input to List — parse_list_input

<dl>

<dt>input_string</dt>
<dd>A string representation of a list.</dd>

</dl>

parse_list_input: Parse String Input to List

Description

Usage

Value

Arguments