combine_rubin

Matrix containing estimated parameters in each imputation
as its rows.

param_imps

List of estimated covariance matrices for each imputation.

cov_imps

Applies Rubin's rules to combine estimates and
variance-covariance matrices from different imputations.

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

combine_rubin function

<dl><dt>param_imps</dt>
<dd>Matrix containing estimated parameters in each imputation
as its rows.</dd>
<dt>cov_imps</dt>
<dd>List of estimated covariance matrices for each imputation.</dd></dl>

Arguments

Combine results from different imputations using Rubin's rules — combine_rubin

<dl>

<dt>param_imps</dt>
<dd>Matrix containing estimated parameters in each imputation
as its rows.</dd>


<dt>cov_imps</dt>
<dd>List of estimated covariance matrices for each imputation.</dd>

</dl>

combine_rubin: Combine results from different imputations using Rubin's rules

Description

Usage

Value

Arguments

References