Robust Structural Equation Modeling with Missing Data and Auxiliary Variables

Documentation for package ‘rsem’ version 0.5.0

rsem-package	Robust Structural Equation Modeling with Missing Data and Auxiliary
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