glm.mids

Applies <code><a href="/link/glm()?package=mice&version=3.16.0" data-mini-rdoc="mice::glm()">glm()</a></code> to a multiply imputed data set

multivariate

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

glm.mids function

<dl><dt>formula</dt>
<dd>a formula expression as for other regression models, of the
form response ~ predictors. See the documentation of <code><a href="/link/lm?package=mice&version=3.16.0" data-mini-rdoc="mice::lm">lm</a></code> and
<code><a href="/link/formula?package=mice&version=3.16.0" data-mini-rdoc="mice::formula">formula</a></code> for details.</dd>
<dt>family</dt>
<dd>The family of the glm model</dd>
<dt>data</dt>
<dd>An object of type <code>mids</code>, which stands for 'multiply imputed
data set', typically created by function <code>mice()</code>.</dd>
<dt>...</dt>
<dd>Additional parameters passed to <code><a href="/link/glm?package=mice&version=3.16.0" data-mini-rdoc="mice::glm">glm</a></code>.</dd></dl>

Arguments

Stef van Buuren, Karin Groothuis-Oudshoorn, 2000

Author

Applies <code><a href='https://rdrr.io/r/stats/glm.html'>glm()</a></code> to a multiply imputed data set

Generalized linear model for mids object — glm.mids

<dl>

<dt>formula</dt>
<dd>a formula expression as for other regression models, of the
form response ~ predictors. See the documentation of <code><a href='https://rdrr.io/r/stats/lm.html'>lm</a></code> and
<code><a href='https://rdrr.io/r/stats/formula.html'>formula</a></code> for details.</dd>


<dt>family</dt>
<dd>The family of the glm model</dd>


<dt>data</dt>
<dd>An object of type <code>mids</code>, which stands for 'multiply imputed
data set', typically created by function <code>mice()</code>.</dd>


<dt>...</dt>
<dd>Additional parameters passed to <code><a href='https://rdrr.io/r/stats/glm.html'>glm</a></code>.</dd>

</dl>

Generalized linear model for <code>mids</code> object

glm.mids: Generalized linear model for `mids` object

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples