sort_by

Sorts a <code>data.frame</code> (ascending by default) based upon variables within the dataset

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 

sort_by function

<dl><dt>df</dt>
<dd>data.frame</dd>
<dt>vars</dt>
<dd>character vector of variables</dd>
<dt>decreasing</dt>
<dd>logical whether sort order should be in descending or ascending (default) order.
Can be either a single logical value (in which case it is applied to
all variables) or a vector which is the same length as <code>vars</code></dd></dl>

Arguments

Sort data.frame — sort_by

<dl>

<dt>df</dt>
<dd>data.frame</dd>


<dt>vars</dt>
<dd>character vector of variables</dd>


<dt>decreasing</dt>
<dd>logical whether sort order should be in descending or ascending (default) order.
Can be either a single logical value (in which case it is applied to
all variables) or a vector which is the same length as <code>vars</code></dd>

</dl>

sort_by: Sort `data.frame`

Description

Usage

Arguments

Examples