A wrapper around <code>if() else()</code> to prevent unexpected
interactions between <code><a href="/link/ifelse()?package=rbmi&version=1.4.1" data-mini-rdoc="rbmi::ifelse()">ifelse()</a></code> and factor variables

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 

ife function

<dl><dt>x</dt>
<dd>True / False</dd>
<dt>a</dt>
<dd>value to return if True</dd>
<dt>b</dt>
<dd>value to return if False</dd></dl>

Arguments

A wrapper around <code>if() else()</code> to prevent unexpected
interactions between <code><a href='https://rdrr.io/r/base/ifelse.html'>ifelse()</a></code> and factor variables

if else — ife

<dl>

<dt>x</dt>
<dd>True / False</dd>


<dt>a</dt>
<dd>value to return if True</dd>


<dt>b</dt>
<dd>value to return if False</dd>

</dl>

ife: if else

Description

Usage

Arguments

Details