as_model_df

Expands out a <code>data.frame</code> using a formula to create a design matrix.
Key details are that it will always place the outcome variable into
the first column of the return object.

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>.

Isaac Gravestock

rbmi

Reference Based Multiple Imputation

Craig Gower-Page

Alessandro Noci

Marcel Wolbers

Daniel Sabanes Bove

F. Hoffmann-La Roche AG 

as_model_df function

<dl><dt>dat</dt>
<dd>a data.frame</dd>
<dt>frm</dt>
<dd>a formula</dd></dl>

Arguments

Expand data.frame into a design matrix — as_model_df

<dl>

<dt>dat</dt>
<dd>a data.frame</dd>


<dt>frm</dt>
<dd>a formula</dd>

</dl>

as_model_df: Expand `data.frame` into a design matrix

Description

Usage

Arguments

Details