combine_models

One or more <code>brmsfit</code> objects.

Optional list of one or more <code>brmsfit</code> objects.

mlist

Logical; indicates if the data should be checked
for being the same across models (defaults to <code>TRUE</code>).
Setting it to <code>FALSE</code> may be useful for instance
when combining models fitted on multiple imputed data sets.

check_data

Combine multiple <code>brmsfit</code> objects, which fitted the same model.
This is usefuly for instance when having manually run models in parallel.

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 non-linear and
smooth terms, auto-correlation structures, censored data, 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 beliefs.
Model fit can easily be assessed and compared with posterior predictive
checks and leave-one-out cross-validation. References: B<c3><bc>rkner (2017)
<doi:10.18637/jss.v080.i01>; B<c3><bc>rkner (2018) <doi:10.32614/RJ-2018-017>;
Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.

combine_models: Combine Models fitted with brms

Description

Usage

Arguments

Value

Details