bmem.sem

Estimate a mediaiton model using SEM technique

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.sem function

<dl> <dt>x</dt>
<dd>A covariance matrix</dd> <dt>ram</dt>
<dd>A path diagram from <code>specify.model</code></dd> <dt>N</dt>
<dd>Sample size</dd> <dt>indirect</dt>
<dd>A vector of indirect effects</dd> <dt>moment</dt>
<dd>Whether mean strucuture is used. The default is FALSE</dd> <dt>...</dt>
<dd>Options that can be supplied to function <code>sem</code>.</dd></dl>

Arguments

Estimate a mediaiton model using SEM technique — bmem.sem

<dl>

 <dt>x</dt>
<dd>A covariance matrix</dd>

 <dt>ram</dt>
<dd>A path diagram from <code>specify.model</code></dd>

 <dt>N</dt>
<dd>Sample size</dd>

 <dt>indirect</dt>
<dd>A vector of indirect effects</dd>

 <dt>moment</dt>
<dd>Whether mean strucuture is used. The default is FALSE</dd>

 <dt>...</dt>
<dd>Options that can be supplied to function <code>sem</code>.</dd>

</dl>

bmem.sem: Estimate a mediaiton model using SEM technique

Description

Usage

Arguments

See Also