fit_model_g

This function fits a generalized linear model using robust estimation methods.
It allows the use of either the 'robust' or 'robustbase' packages for fitting
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 

fit_model_g function

<dl><dt>engine</dt>
<dd>A character string specifying the engine to be used for model
fitting. Must be either "robust" or "robustbase".</dd>
<dt>formula</dt>
<dd>An object of class formula (or one that can be coerced to that
class): a symbolic description of the model to be fitted.</dd>
<dt>data</dt>
<dd>A dataframe containing the variables in the model.</dd>
<dt>family</dt>
<dd>A description of the error distribution and link function to be
used in the model (See stats::family for details of family
functions).</dd>
<dt>method</dt>
<dd>Fitting method to be used. Can vary depending on the selected
engine.</dd>
<dt>...</dt>
<dd>Additional arguments to be passed to the underlying fitting
function.</dd></dl>

Arguments

Fit a Generalized Linear Model with Robust Estimation — fit_model_g

<dl>

<dt>engine</dt>
<dd>A character string specifying the engine to be used for model
fitting. Must be either "robust" or "robustbase".</dd>


<dt>formula</dt>
<dd>An object of class formula (or one that can be coerced to that
class): a symbolic description of the model to be fitted.</dd>


<dt>data</dt>
<dd>A dataframe containing the variables in the model.</dd>


<dt>family</dt>
<dd>A description of the error distribution and link function to be
used in the model (See stats::family for details of family
functions).</dd>


<dt>method</dt>
<dd>Fitting method to be used. Can vary depending on the selected
engine.</dd>


<dt>...</dt>
<dd>Additional arguments to be passed to the underlying fitting
function.</dd>

</dl>

fit_model_g: Fit a Generalized Linear Model with Robust Estimation

Description

Usage

Value

Arguments