mice_impute_once

Imputes a single dataset using mice

internal

Impute the covariance matrix of incomplete data so that factor
analysis can be performed. Imputations are made using multiple imputation
by Multivariate Imputation with Chained Equations (MICE) and combined with
Rubin's rules. Parametric Fieller confidence intervals and nonparametric
bootstrap confidence intervals can be obtained for the variance explained by
different numbers of principal components. The method is described in
Nassiri et al. (2018) <doi:10.3758/s13428-017-1013-4>.

Tobias Busch

mifa

Multiple Imputation for Exploratory Factor Analysis

Vahid Nassiri

Anikó Lovik

Geert  Molenberghs

Geert  Verbeke

mice_impute_once function

<dl><dt>data</dt>
<dd>A data frame with missing values coded as <code>NA</code>.</dd></dl>

Arguments

Imputes a single dataset using mice — mice_impute_once

<dl>

<dt>data</dt>
<dd>A data frame with missing values coded as <code>NA</code>.</dd>

</dl>

mice_impute_once: Imputes a single dataset using mice

Description

Usage

Value

Arguments