qbrms_ordinal_binary

Splits an ordered response with K levels into K-1 binary problems
(thresholds y &gt; c_j) and fits a simple binomial GLM for each split.

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

qbrms_ordinal_binary function

<dl><dt>formula</dt>
<dd>Model formula with an ordered response on the LHS.</dd>
<dt>data</dt>
<dd>Data frame.</dd>
<dt>verbose</dt>
<dd>Logical; print progress messages.</dd>
<dt>...</dt>
<dd>Ignored (compat).</dd></dl>

Arguments

Ordinal regression via binary decomposition (fallback) — qbrms_ordinal_binary

<dl>

<dt>formula</dt>
<dd>Model formula with an ordered response on the LHS.</dd>


<dt>data</dt>
<dd>Data frame.</dd>


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


<dt>...</dt>
<dd>Ignored (compat).</dd>

</dl>

qbrms_ordinal_binary: Ordinal regression via binary decomposition (fallback)

Description

Usage

Value

Arguments