get_stan_model

Gets a compiled Stan object that can be used with <code>rstan::sampling()</code>,
based on the choice of the covariance structure and the prior on the parameters.

internal

Implements standard and reference based multiple imputation methods for continuous
longitudinal endpoints (Gower-Page et al. (2022) <doi:10.21105/joss.04251>). In particular,
this package supports deterministic conditional mean imputation and jackknifing as described
in Wolbers et al. (2022) <doi:10.1002/pst.2234>, Bayesian multiple imputation as described
in Carpenter et al. (2013) <doi:10.1080/10543406.2013.834911>, and bootstrapped maximum
likelihood imputation as described in von Hippel and Bartlett (2021) <doi: 10.1214/20-STS793>.

Craig Gower-Page

rbmi

Reference Based Multiple Imputation

Isaac Gravestock

Alessandro Noci

Marcel Wolbers

Daniel Sabanes Bove

F. Hoffmann-La Roche AG 

get_stan_model function

<dl><dt>covariance</dt>
<dd>A string indicating the covariance structure to be used.</dd>
<dt>prior_cov</dt>
<dd>A string indicating the prior on the covariance parameters.</dd></dl>

Arguments

Get Compiled Stan Object — get_stan_model

<dl>

<dt>covariance</dt>
<dd>A string indicating the covariance structure to be used.</dd>


<dt>prior_cov</dt>
<dd>A string indicating the prior on the covariance parameters.</dd>

</dl>

get_stan_model: Get Compiled Stan Object

Description

Usage

Value

Arguments