bmem.em.rcov

Estimation of robust covariance matrix

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.rcov function

<dl> <dt>xmis</dt>
<dd>Missing data pattern</dd> <dt>varphi</dt>
<dd>Percent of data to be downweighted</dd> <dt>moment</dt>
<dd>Moment analysis if TRUE</dd> <dt>max_it</dt>
<dd>Maximum number of iteration</dd> <dt>st</dt>
<dd>Starting values</dd></dl>

Arguments

Author

Estimation of robust covariance matrix — bmem.em.rcov

<dl>

 <dt>xmis</dt>
<dd>Missing data pattern</dd>

 <dt>varphi</dt>
<dd>Percent of data to be downweighted</dd>

 <dt>moment</dt>
<dd>Moment analysis if TRUE</dd>

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

 <dt>st</dt>
<dd>Starting values</dd>

</dl>

bmem.em.rcov: Estimation of robust covariance matrix

Description

Usage

Value

Arguments

Author