validate.references

Checks to ensure that the user specified references are
expect values (i.e. those found within the source data).

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

Alessandro Noci

Marcel Wolbers

Isaac Gravestock

F. Hoffmann-La Roche AG 

validate.references function

<dl><dt>x</dt>
<dd>named character vector.</dd>
<dt>control</dt>
<dd>factor variable (should be the <code>group</code> variable from the source dataset).</dd>
<dt>...</dt>
<dd>Not used.</dd></dl>

Arguments

Validate user supplied references — validate.references

<dl>

<dt>x</dt>
<dd>named character vector.</dd>


<dt>control</dt>
<dd>factor variable (should be the <code>group</code> variable from the source dataset).</dd>


<dt>...</dt>
<dd>Not used.</dd>

</dl>

validate.references: Validate user supplied references

Description

Usage

Value

Arguments