p_significance

Compute the probability that each parameter is above a threshold
in the median's direction, similar to bayestestR::p_significance().
This represents the proportion of the posterior distribution that
indicates a "significant" effect in the median's direction.

Provides a 'brms'-like interface for fitting Bayesian regression models
using 'INLA' (Integrated Nested Laplace Approximations) and 'TMB' (Template Model Builder).
The package offers faster model fitting while maintaining familiar 'brms' syntax and
output formats. Supports fixed and mixed effects models, multiple probability distributions,
conditional effects plots, and posterior predictive checks with summary methods compatible
with 'brms'. 'TMB' integration provides fast ordinal regression capabilities. Implements
methods adapted from 'emmeans' for marginal means estimation and 'bayestestR' for Bayesian
inference assessment. Methods are based on Rue et al. (2009) <doi:10.1111/j.1467-9868.2008.00700.x>,
Kristensen et al. (2016) <doi:10.18637/jss.v070.i05>, Lenth (2016) <doi:10.18637/jss.v069.i01>,
Bürkner (2017) <doi:10.18637/jss.v080.i01>, Makowski et al. (2019) <doi:10.21105/joss.01541>,
and Kruschke (2014, ISBN:9780124058880).

Tony Myers

qbrms

Quick Bayesian Regression Models Using 'INLA' with 'brms' Syntax

p_significance function

<dl><dt>object</dt>
<dd>A <code>qbrms_fit</code> object.</dd>
<dt>parameters</dt>
<dd>Optional character vector of parameter names; if <code>NULL</code>,
all fixed-effect coefficients are used.</dd>
<dt>threshold</dt>
<dd>The threshold value that separates significant from negligible effect:<ul>
<li><code>"default"</code>: Uses 0.1 as threshold range around zero</li>
<li>A single numeric value (e.g., 0.1): Creates symmetric range around zero (-0.1, 0.1)</li>
<li>A numeric vector of length two (e.g., c(-0.2, 0.1)): Asymmetric threshold</li>
<li>A list of numeric vectors: Each vector corresponds to a parameter</li>
<li>A named list: Names correspond to parameter names</li>
</ul></dd>
<dt>nsim</dt>
<dd>Number of draws to simulate for the approximation.</dd>
<dt>verbose</dt>
<dd>Logical; print progress information.</dd></dl>

Arguments

Probability of Practical Significance (Enhanced bayestestR-style) — p_significance

<dl>

<dt>object</dt>
<dd>A <code>qbrms_fit</code> object.</dd>


<dt>parameters</dt>
<dd>Optional character vector of parameter names; if <code>NULL</code>,
all fixed-effect coefficients are used.</dd>


<dt>threshold</dt>
<dd>The threshold value that separates significant from negligible effect:<ul>
<li><code>"default"</code>: Uses 0.1 as threshold range around zero</li>
<li>A single numeric value (e.g., 0.1): Creates symmetric range around zero (-0.1, 0.1)</li>
<li>A numeric vector of length two (e.g., c(-0.2, 0.1)): Asymmetric threshold</li>
<li>A list of numeric vectors: Each vector corresponds to a parameter</li>
<li>A named list: Names correspond to parameter names</li>
</ul></dd>


<dt>nsim</dt>
<dd>Number of draws to simulate for the approximation.</dd>


<dt>verbose</dt>
<dd>Logical; print progress information.</dd>

</dl>

p_significance: Probability of Practical Significance (Enhanced bayestestR-style)

Description

Usage

Value

Arguments