resolve_contrast_weights

Expands a (possibly level-named or level-length) numeric weight vector into a full
vector over all group levels in factor order, validating that it references known
levels, sums to zero and is not trivially zero.

internal

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>.

Lukas A. Widmer

rbmi

Reference Based Multiple Imputation

Craig Gower-Page

Isaac Gravestock

Alessandro Noci

Marcel Wolbers

Daniel Sabanes Bove

F. Hoffmann-La Roche AG 

resolve_contrast_weights function

<dl><dt>x</dt>
<dd>Numeric weight vector, either named by group levels (missing levels are
filled with <code>0</code>) or of length <code>length(orig_levels)</code> in factor order.</dd>
<dt>orig_levels</dt>
<dd>Character vector of the group factor levels (in order).</dd></dl>

Arguments

Resolve a numeric contrast weight vector to full group-level order — resolve_contrast_weights

<dl>

<dt>x</dt>
<dd>Numeric weight vector, either named by group levels (missing levels are
filled with <code>0</code>) or of length <code>length(orig_levels)</code> in factor order.</dd>


<dt>orig_levels</dt>
<dd>Character vector of the group factor levels (in order).</dd>

</dl>

resolve_contrast_weights: Resolve a numeric contrast weight vector to full group-level order

Description

Usage

Value

Arguments