fail_drop

This internal function is designed to handle failures in cluster-specific model
fitting and variable dropping issues in the context of cluster-adjusted robust
inference functions. It checks for model fitting failures and whether independent
variables have been dropped in the model.

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 

fail_drop function

<dl><dt>drop</dt>
<dd>Logical; if TRUE, allows the function to return <code>NA</code> for failed
model fits, otherwise stops execution with an error message.</dd>
<dt>fail</dt>
<dd>Logical; indicates whether the model fitting process has failed.</dd>
<dt>clust.mod</dt>
<dd>A model object resulting from cluster-specific fitting.</dd>
<dt>ind_variables</dt>
<dd>A character vector of independent variable names expected
in the model.</dd></dl>

Arguments

Handle Model Fitting Failures and Variable Dropping — fail_drop

<dl>

<dt>drop</dt>
<dd>Logical; if TRUE, allows the function to return <code>NA</code> for failed
model fits, otherwise stops execution with an error message.</dd>


<dt>fail</dt>
<dd>Logical; indicates whether the model fitting process has failed.</dd>


<dt>clust.mod</dt>
<dd>A model object resulting from cluster-specific fitting.</dd>


<dt>ind_variables</dt>
<dd>A character vector of independent variable names expected
in the model.</dd>

</dl>

fail_drop: Handle Model Fitting Failures and Variable Dropping

Description

Usage

Value

Arguments