conditional_effects_slices

Build point/interval summaries at a few values of a numeric moderator,
plotted against the factor on the x-axis.

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

conditional_effects_slices function

<dl><dt>object</dt>
<dd>A qbrms_fit object.</dd>
<dt>effects</dt>
<dd>Character vector specifying effects to plot. If NULL, all numeric predictors are used.</dd>
<dt>slices</dt>
<dd>Named list of variables and values at which to slice the data.</dd>
<dt>nslices</dt>
<dd>Number of slices to use for each slicing variable.</dd>
<dt>prob</dt>
<dd>Probability mass to include in uncertainty intervals (default 0.95).</dd>
<dt>ndraws</dt>
<dd>Number of posterior draws to use for predictions.</dd>
<dt>at</dt>
<dd>Named list of values at which to fix other predictors.</dd>
<dt>seed</dt>
<dd>Random seed for reproducibility.</dd>
<dt>...</dt>
<dd>Additional arguments passed to prediction functions.</dd></dl>

Arguments

Discrete-slice conditional effects (brms-style) for qbrms — conditional_effects_slices

<dl>

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


<dt>effects</dt>
<dd>Character vector specifying effects to plot. If NULL, all numeric predictors are used.</dd>


<dt>slices</dt>
<dd>Named list of variables and values at which to slice the data.</dd>


<dt>nslices</dt>
<dd>Number of slices to use for each slicing variable.</dd>


<dt>prob</dt>
<dd>Probability mass to include in uncertainty intervals (default 0.95).</dd>


<dt>ndraws</dt>
<dd>Number of posterior draws to use for predictions.</dd>


<dt>at</dt>
<dd>Named list of values at which to fix other predictors.</dd>


<dt>seed</dt>
<dd>Random seed for reproducibility.</dd>


<dt>...</dt>
<dd>Additional arguments passed to prediction functions.</dd>

</dl>

conditional_effects_slices: Discrete-slice conditional effects (brms-style) for qbrms

Description

Usage

Value

Arguments