bmem.ci.bc1

Bias-corrected confidence intervals (for a single variable)

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.ci.bc1 function

<dl> <dt>x</dt>
<dd>A vector from a bootstrap output.</dd> <dt>b</dt>
<dd>Parameter estimate from the original sample</dd> <dt>cl</dt>
<dd>Confidence level. Default 0.95.</dd></dl>

Arguments

Author

Bias-corrected confidence intervals (for a single variable) — bmem.ci.bc1

<dl>

 <dt>x</dt>
<dd>A vector from a bootstrap output.</dd>

 <dt>b</dt>
<dd>Parameter estimate from the original sample</dd>

 <dt>cl</dt>
<dd>Confidence level. Default 0.95.</dd>

</dl>

bmem.ci.bc1: Bias-corrected confidence intervals (for a single variable)

Description

Usage

Arguments

Author

See Also