rsem.fit

A robust procedure is implemented to estimate means and covariance matrix of multiple variables with missing data using Huber weight and then to estimate a structural equation model.

Zhiyong Zhang

rsem

Robust Structural Equation Modeling with Missing Data and
Auxiliary Variables

rsem.fit function

<dl><dt>object</dt>
<dd>Output from lavaan analysis, such as growth, factor, sem functions.</dd> <dt>gamma</dt>
<dd>Robust covariance matrix for saturated mean and covariances</dd>
 <dt>musig</dt>
<dd>Robust saturated mean and covariances</dd></dl>

Arguments

Author

Calculate robust test statistics — rsem.fit

<dl>

<dt>object</dt>
<dd>Output from lavaan analysis, such as growth, factor, sem functions.</dd>

 <dt>gamma</dt>
<dd>Robust covariance matrix for saturated mean and covariances</dd>


 <dt>musig</dt>
<dd>Robust saturated mean and covariances</dd>

</dl>

rsem.fit: Calculate robust test statistics

Description

Usage

Arguments

Author

References

Examples