standata.brmsfit

Extract all data that was used by Stan to fit a brms model.

Fit Bayesian generalized (non-)linear multivariate multilevel models
using 'Stan' for full Bayesian inference. A wide range of distributions
and link functions are supported, allowing users to fit -- among others --
linear, robust linear, count data, survival, response times, ordinal,
zero-inflated, hurdle, and even self-defined mixture models all in a
multilevel context. Further modeling options include both theory-driven and
data-driven non-linear terms, auto-correlation structures, censoring and
truncation, meta-analytic standard errors, and quite a few more.
In addition, all parameters of the response distribution can be predicted
in order to perform distributional regression. Prior specifications are
flexible and explicitly encourage users to apply prior distributions that
actually reflect their prior knowledge. Models can easily be evaluated and
compared using several methods assessing posterior or prior predictions.
References: Bürkner (2017) <doi:10.18637/jss.v080.i01>;
Bürkner (2018) <doi:10.32614/RJ-2018-017>;
Bürkner (2021) <doi:10.18637/jss.v100.i05>; Carpenter et al. (2017)
<doi:10.18637/jss.v076.i01>.

PaulChristian Buerkner

brms

Bayesian Regression Models using 'Stan'

Paul-Christian Bürkner

Jonah Gabry

Sebastian Weber

Andrew Johnson

Martin Modrak

Hamada S. Badr

Frank Weber

Aki Vehtari

Mattan S. Ben-Shachar

Hayden Rabel

Simon C. Mills

Stephen Wild

Ven Popov

standata.brmsfit function

<dl><dt>object</dt>
<dd>An object of class <code>brmsfit</code>.</dd>
<dt>newdata</dt>
<dd>An optional data.frame for which to evaluate predictions. If
<code>NULL</code> (default), the original data of the model is used. <code>NA</code>
values within factors (excluding grouping variables) are interpreted as if
all dummy variables of this factor are zero. This allows, for instance, to
make predictions of the grand mean when using sum coding. <code>NA</code> values
within grouping variables are treated as a new level.</dd>
<dt>re_formula</dt>
<dd>formula containing group-level effects to be considered in
the prediction. If <code>NULL</code> (default), include all group-level effects;
if <code>NA</code> or <code>~0</code>, include no group-level effects.</dd>
<dt>newdata2</dt>
<dd>A named <code>list</code> of objects containing new data, which
cannot be passed via argument <code>newdata</code>. Required for some objects
used in autocorrelation structures, or <code>stanvars</code>.</dd>
<dt>new_objects</dt>
<dd>Deprecated alias of <code>newdata2</code>.</dd>
<dt>incl_autocor</dt>
<dd>A flag indicating if correlation structures originally
specified via <code>autocor</code> should be included in the predictions.
Defaults to <code>TRUE</code>.</dd>
<dt>...</dt>
<dd>More arguments passed to
<code>standata.default</code>.
and <code>validate_newdata</code>.</dd></dl>

Arguments

Extract data passed to Stan from brmsfit objects — standata.brmsfit

<dl>

<dt>object</dt>
<dd>An object of class <code>brmsfit</code>.</dd>


<dt>newdata</dt>
<dd>An optional data.frame for which to evaluate predictions. If
<code>NULL</code> (default), the original data of the model is used. <code>NA</code>
values within factors (excluding grouping variables) are interpreted as if
all dummy variables of this factor are zero. This allows, for instance, to
make predictions of the grand mean when using sum coding. <code>NA</code> values
within grouping variables are treated as a new level.</dd>


<dt>re_formula</dt>
<dd>formula containing group-level effects to be considered in
the prediction. If <code>NULL</code> (default), include all group-level effects;
if <code>NA</code> or <code>~0</code>, include no group-level effects.</dd>


<dt>newdata2</dt>
<dd>A named <code>list</code> of objects containing new data, which
cannot be passed via argument <code>newdata</code>. Required for some objects
used in autocorrelation structures, or <code>stanvars</code>.</dd>


<dt>new_objects</dt>
<dd>Deprecated alias of <code>newdata2</code>.</dd>


<dt>incl_autocor</dt>
<dd>A flag indicating if correlation structures originally
specified via <code>autocor</code> should be included in the predictions.
Defaults to <code>TRUE</code>.</dd>


<dt>...</dt>
<dd>More arguments passed to
<code>standata.default</code>.
and <code>validate_newdata</code>.</dd>

</dl>

Extract data passed to Stan from <code>brmsfit</code> objects

standata.brmsfit: Extract data passed to Stan from `brmsfit` objects

Description

Usage

Value

Arguments