bmem.mi.cov

Covariance estimation for multiple imputation

Four methods for mediation analysis with missing data: Listwise deletion, Pairwise deletion, Multiple imputation, and Two Stage Maximum Likelihood algorithm. For MI and TS-ML, auxiliary variables can be included. Bootstrap confidence intervals for mediation effects are obtained. The robust method is also implemented for TS-ML. Since version 1.4, bmem adds the capability to conduct power analysis for mediation models. Details about the methods used can be found in these articles. Zhang and Wang (2003) <doi:10.1007/s11336-012-9301-5>. Zhang (2014) <doi:10.3758/s13428-013-0424-0>.

Zhiyong Zhang

bmem

Mediation Analysis with Missing Data Using Bootstrap

bmem.mi.cov function

<dl> <dt>x</dt>
<dd>A data set</dd> <dt>m</dt>
<dd>Number of imputations</dd> <dt>moment</dt>
<dd>Estimate mean or not</dd></dl>

Arguments

Covariance estimation for multiple imputation — bmem.mi.cov

<dl>

 <dt>x</dt>
<dd>A data set</dd>

 <dt>m</dt>
<dd>Number of imputations</dd>

 <dt>moment</dt>
<dd>Estimate mean or not</dd>

</dl>

bmem.mi.cov: Covariance estimation for multiple imputation

Description

Usage

Arguments