bmem.em.cov

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.em.cov function

<dl> <dt>xmis</dt>
<dd>An object from output of <code>bmem.pattern</code>.</dd> <dt>moment</dt>
<dd>Whether estimating mean</dd> <dt>max_it</dt>
<dd>Maximum number of iterations</dd></dl>

Arguments

Covariance matrix from EM — bmem.em.cov

<dl>

 <dt>xmis</dt>
<dd>An object from output of <code>bmem.pattern</code>.</dd>

 <dt>moment</dt>
<dd>Whether estimating mean</dd>

 <dt>max_it</dt>
<dd>Maximum number of iterations</dd>

</dl>

bmem.em.cov: Covariance matrix from EM

Description

Usage

Arguments