squeeze

A numerical vector of length 2 containing the lower and upper bounds. 
By default, the bounds are to the minimum and maximum values in <code>x</code>.

bounds

A logical vector of length <code>length(x)</code> that is used to select a 
subset in <code>x</code> before calculating automatic bounds.

This function replaces any values in <code>x</code> that are lower than 
<code>bounds[1]</code> by <code>bounds[1]</code>, and replaces any values higher 
than <code>bounds[2]</code> by <code>bounds[2]</code>.

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

Alexander Robitzsch

Gerko Vink

Lisa Doove

Shahab Jolani

Rianne Schouten

Philipp Gaffert

Florian Meinfelder

Bernie Gray

squeeze function

Squeeze the imputed values to be within specified boundaries. — squeeze

Squeeze the imputed values to be within specified boundaries.

squeeze: Squeeze the imputed values to be within specified boundaries.

Description

Usage

Arguments

Value