R: Robust Structural Equation Modeling with Missing Data and Auxiliary Variables

# Robust Structural Equation Modeling with Missing Data and Auxiliary Variables

## Documentation for package ‘rsem’ version 0.5.1

- DESCRIPTION file

## Help Pages

rsem-package | Robust Structural Equation Modeling with Missing Data and Auxiliary Variables
mardiamv25 | Simulated data
mardiamv25_contaminated | Simulated data
rsem | The main function for robust SEM analysis
rsem.Ascov | Sandwich-type covariance matrix
rsem.DP | Generate a duplication matrix
rsem.emmusig | Robust mean and covariance matrix using Huber-type weight
rsem.fit | Calculate robust test statistics
rsem.gname | Internal function
rsem.index | rsem.index function
rsem.indexv | rsem.indexv function
rsem.indexvc | rsem.indexvc function
rsem.lavaan | Conduct robust SEM analysis using lavaan
rsem.pattern | Obtaining missing data patterns
rsem.print | Organize the output for Lavaan with robust s.e. and test statistics
rsem.se | Calculate robust standard errors
rsem.ssq | Calculate the squared sum of a matrix
rsem.switch | swith function
rsem.switch.gamma | Internal function
rsem.vec | Stacking a matrix to a vector
rsem.vech | Stacking lower triange of a matrix to a vector
rsem.weight | Calculate weight for each subject
semdiag.call.eqs | Run EQS from R
semdiag.combinations | Enumerate the Combinations of the Elements of a Vector
semdiag.read.eqs | Import of EQS outputs into R
semdiag.run.eqs | Run EQS from R