make.predictorMatrix

This helper function creates a valid <code>predictMatrix</code>. The
<code>predictorMatrix</code> is an argument to the <code>mice</code> function.
It specifies the target variable or block in the rows, and the
predictor variables on the columns. An entry of <code>0</code> means that
the column variable is NOT used to impute the row variable or block.
A nonzero value indicates that it is used.

Multiple imputation using Fully Conditional Specification (FCS)
implemented by the MICE algorithm as described in Van Buuren and
Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. Each variable has
its own imputation model. Built-in imputation models are provided for
continuous data (predictive mean matching, normal), binary data (logistic
regression), unordered categorical data (polytomous logistic regression)
and ordered categorical data (proportional odds). MICE can also impute
continuous two-level data (normal model, pan, second-level variables).
Passive imputation can be used to maintain consistency between variables.
Various diagnostic plots are available to inspect the quality of the
imputations.

Stef van Buuren

mice

Multivariate Imputation by Chained Equations

Karin Groothuis-Oudshoorn

Gerko Vink

Rianne Schouten

Alexander Robitzsch

Patrick Rockenschaub

Lisa Doove

Shahab Jolani

Margarita Moreno-Betancur

Ian White

Philipp Gaffert

Florian Meinfelder

Bernie Gray

Vincent Arel-Bundock

Mingyang Cai

Thom Volker

Edoardo Costantini

Caspar van Lissa

Hanne Oberman

Stephen Wade

make.predictorMatrix function

<dl><dt>data</dt>
<dd>A <code>data.frame</code> with the source data</dd>
<dt>blocks</dt>
<dd>An optional specification for blocks of variables in
the rows. The default assigns each variable in its own block.</dd>
<dt>predictorMatrix</dt>
<dd>A predictor matrix from which rows with the same
names are copied into the output predictor matrix.</dd></dl>

Arguments

Creates a predictorMatrix argument — make.predictorMatrix

<dl>

<dt>data</dt>
<dd>A <code>data.frame</code> with the source data</dd>


<dt>blocks</dt>
<dd>An optional specification for blocks of variables in
the rows. The default assigns each variable in its own block.</dd>


<dt>predictorMatrix</dt>
<dd>A predictor matrix from which rows with the same
names are copied into the output predictor matrix.</dd>

</dl>

Creates a <code>predictorMatrix</code> argument

make.predictorMatrix: Creates a `predictorMatrix` argument

Description

Usage

Value

Arguments

See Also

Examples