BFF.object

<p>The BFF object is a class that contains the results of a Bayes Factor Function.
The BFF object contains the following fields:</p><table class="table">
<tr><td><code>BFF</code></td><td>the object containing the log_bf (log Bayes factor values) and corresponding omega values</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>input</code></td><td>the object containing the input values</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>log_bf_h1</code></td><td>maximized Bayes factor in favor of the alternative, or the corresponding Bayes factor if an omega is supplied</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>omega_h1</code></td><td>corresponding omega value for maximized Bayes factor in favor of the alternative, orthe corresponding omega for the Bayes factor if an omega is supplied</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>log_bf_h0</code></td><td>minimized Bayes factor in favor of the null (for medium or large effect sizes, only returned if a specific omega is not set)</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>omega_h0</code></td><td>corresponding omega value for minimized Bayes factor in favor of the null (for medium or large effect sizes, only returned if a specific omega is not set)</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>alternative</code></td><td>alternative hypothesis used in calculations</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>omega_set</code></td><td>was an omega value provided?</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>r</code></td><td>r value (default is 1 if not provided by user)</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>test_type</code></td><td>type of BFF test</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>generic_test</code></td><td>FALSE</td></tr>
<tr><td></td><td></td></tr>
</table><p></p><p></p>

Bayes factors represent the ratio of probabilities assigned to data by competing scientific hypotheses. However, one drawback of Bayes factors is their dependence on prior specifications that define null and alternative hypotheses. Additionally, there are challenges in their computation. To address these issues, we define Bayes factor functions (BFFs) directly from common test statistics. BFFs express Bayes factors as a function of the prior densities used to define the alternative hypotheses. These prior densities are centered on standardized effects, which serve as indices for the BFF. Therefore, BFFs offer a summary of evidence in favor of alternative hypotheses that correspond to a range of scientifically interesting effect sizes. Such summaries remove the need for arbitrary thresholds to determine "statistical significance." BFFs are available in closed form and can be easily computed from z, t, chi-squared, and F statistics. They depend on hyperparameters "r" and "tau^2", which determine the shape and scale of the prior distributions defining the alternative hypotheses. Plots of BFFs versus effect size provide informative summaries of hypothesis tests that can be easily aggregated across studies.

Rachael Shudde

Bayes Factor Functions

František Bartoš

Saptati Datta

Riana Guha

Sandy Pramanik

Valen Johnson

BFF.object function

<p>The BFF object is a class that contains the results of a Bayes Factor Function.
The BFF object contains the following fields:</p><table class='table'>
<tr><td><code>BFF</code></td><td>the object containing the log_bf (log Bayes factor values) and corresponding omega values</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>input</code></td><td>the object containing the input values</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>log_bf_h1</code></td><td>maximized Bayes factor in favor of the alternative, or the corresponding Bayes factor if an omega is supplied</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>omega_h1</code></td><td>corresponding omega value for maximized Bayes factor in favor of the alternative, orthe corresponding omega for the Bayes factor if an omega is supplied</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>log_bf_h0</code></td><td>minimized Bayes factor in favor of the null (for medium or large effect sizes, only returned if a specific omega is not set)</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>omega_h0</code></td><td>corresponding omega value for minimized Bayes factor in favor of the null (for medium or large effect sizes, only returned if a specific omega is not set)</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>alternative</code></td><td>alternative hypothesis used in calculations</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>omega_set</code></td><td>was an omega value provided?</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>r</code></td><td>r value (default is 1 if not provided by user)</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>test_type</code></td><td>type of BFF test</td></tr>
<tr><td></td><td></td></tr>
<tr><td><code>generic_test</code></td><td>FALSE</td></tr>
<tr><td></td><td></td></tr>
</table>



BFF.object: BFF Object

Description

Arguments

`BFF`	the object containing the log_bf (log Bayes factor values) and corresponding omega values

`input`	the object containing the input values

`log_bf_h1`	maximized Bayes factor in favor of the alternative, or the corresponding Bayes factor if an omega is supplied

`omega_h1`	corresponding omega value for maximized Bayes factor in favor of the alternative, orthe corresponding omega for the Bayes factor if an omega is supplied

`log_bf_h0`	minimized Bayes factor in favor of the null (for medium or large effect sizes, only returned if a specific omega is not set)

`omega_h0`	corresponding omega value for minimized Bayes factor in favor of the null (for medium or large effect sizes, only returned if a specific omega is not set)

`alternative`	alternative hypothesis used in calculations

`omega_set`	was an omega value provided?

`r`	r value (default is 1 if not provided by user)

`test_type`	type of BFF test

`generic_test`	FALSE