mmibain

The user can upload CSV data; choose a model engine (lm, t_test,
lavaan); specify the formula, variables, or model; and provide additional
arguments. Once the model is fitted, the app allows for setting up hypotheses
for evaluation. Upon running the analysis, it displays the results of the
Bayesian Informative Hypotheses Evaluation.

Researchers often have expectations about the relations between means
of different groups or standardized regression coefficients; using informative
hypothesis testing to incorporate these expectations into the analysis through
order constraints increases statistical power
Vanbrabant and Rosseel (2020) <doi:10.4324/9780429273872-14>. Another valuable
tool, the Bayes factor, can evaluate evidence for multiple hypotheses without
concerns about multiple testing, and can be used in Bayesian updating
Hoijtink, Mulder, van Lissa & Gu (2019) <doi:10.1037/met0000201>. The 'bain'
R package enables informative hypothesis testing using the Bayes factor. The
'mmibain' package provides 'shiny' web applications based on 'bain'. The
RepliCrisis() function launches a 'shiny' card game to simulate the evaluation
of replication studies while the mmibain() function launches a 'shiny'
application to fit Bayesian informative hypotheses evaluation models from
'bain'.

Mackson Ncube

Bayesian Informative Hypotheses Evaluation Web Applications

mightymetrika, LLC 

mmibain function

<ul>
<li>Data upload (CSV format).</li>
<li>Engine selection (lm, t_test, lavaan).</li>
<li>Model input based on chosen engine.</li>
<li>Additional arguments for statistical model function.</li>
<li>Action button to fit the model.</li>
<li>Hypotheses input.</li>
<li>Fraction input for the <code>bain</code> fraction parameter.</li>
<li>Option to evaluate hypotheses with respect to standardized regression
coefficients.</li>
<li>Confidence interval input.</li>
<li>Seed input for reproducibility.</li>
<li>Action button to run the Bayesian Informative Hypotheses Evaluation.</li>
</ul>

UI Components

mmibain Shiny App — mmibain

<ul>
<li>Data upload (CSV format).</li>
<li>Engine selection (lm, t_test, lavaan).</li>
<li>Model input based on chosen engine.</li>
<li>Additional arguments for statistical model function.</li>
<li>Action button to fit the model.</li>
<li>Hypotheses input.</li>
<li>Fraction input for the <code>bain</code> fraction parameter.</li>
<li>Option to evaluate hypotheses with respect to standardized regression
coefficients.</li>
<li>Confidence interval input.</li>
<li>Seed input for reproducibility.</li>
<li>Action button to run the Bayesian Informative Hypotheses Evaluation.</li>
</ul>

mmibain: mmibain Shiny App

Description

Usage

Arguments

Value

UI Components

Details

References

See Also

Examples