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rsem (version 0.4.6)

Robust Structural Equation Modeling with Missing Data and Auxiliary Variables

Description

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.

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Version

Install

install.packages('rsem')

Monthly Downloads

353

Version

0.4.6

License

GPL-2

Maintainer

Zhiyong Zhang

Last Published

May 15th, 2015

Functions in rsem (0.4.6)

rsem-package

Robust Structural Equation Modeling with Missing Data and Auxiliary
rsem.fit

Calculate robust test statistics
rsem.index

rsem.index function
rsem.pattern

Obtaining missing data patterns
rsem.weight

Calculate weight for each subject
rsem.indexvc

rsem.indexvc function
rsem.Ascov

Sandwich-type covariance matrix
semdiag.read.eqs

Import of EQS outputs into R
rsem.se

Calculate robust standard errors
rsem

The main function for robust SEM analysis
rsem.switch

swith function
rsem.gname

Internal function
rsem.ssq

Calculate the squared sum of a matrix
rsem.lavaan

Conduct robust SEM analysis using lavaan
rsem.print

Organize the output for Lavaan with robust s.e. and test statistics
rsem.vec

Stacking a matrix to a vector
semdiag.run.eqs

Run EQS from R
rsem.vech

Stacking lower triange of a matrix to a vector
semdiag.combinations

Enumerate the Combinations of the Elements of a Vector
rsem.indexv

rsem.indexv function
rsem.DP

Generate a duplication matrix
mardiamv25

Simulated data
rsem.emmusig

Robust mean and covariance matrix using Huber-type weight
rsem.switch.gamma

Internal function