as_mmrm_formula

Derives the MMRM model formula from the structure of mmrm_df.
returns a formula object of the form:

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 

as_mmrm_formula function

<dl><dt>mmrm_df</dt>
<dd>an mmrm <code>data.frame</code> as created by <code>as_mmrm_df()</code></dd>
<dt>cov_struct</dt>
<dd>Character - The covariance structure to be used, must be one of <code>"us"</code> (default),
<code>"ad"</code>, <code>"adh"</code>, <code>"ar1"</code>, <code>"ar1h"</code>, <code>"cs"</code>, <code>"csh"</code>, <code>"toep"</code>, or <code>"toeph"</code>)</dd></dl>

Arguments

Create MMRM formula — as_mmrm_formula

<dl>

<dt>mmrm_df</dt>
<dd>an mmrm <code>data.frame</code> as created by <code>as_mmrm_df()</code></dd>


<dt>cov_struct</dt>
<dd>Character - The covariance structure to be used, must be one of <code>"us"</code> (default),
<code>"ad"</code>, <code>"adh"</code>, <code>"ar1"</code>, <code>"ar1h"</code>, <code>"cs"</code>, <code>"csh"</code>, <code>"toep"</code>, or <code>"toeph"</code>)</dd>

</dl>

as_mmrm_formula: Create MMRM formula

Description

Usage

Arguments

Details