rsem: The main function for robust SEM analysis

In rsem: Robust Structural Equation Modeling with Missing Data and Auxiliary Variables

The main function for robust SEM analysis

Description

This is the function to carry out all analysis.

Usage

rsem(dset, select, EQSmodel, moment=TRUE, varphi=.1, st='i', max.it=1000, 
eqsdata='data.txt', eqsweight='weight.txt', EQSpgm="C:/Progra~1/EQS61/WINEQS.EXE", 
serial="1234")

Arguments

dset	A data matrix or a data frame
select	Variables to be seleted for SEM analysis. If omitted, all variables in the data set will be used.
moment	With mean structure. For covariance only, set moment=FALSE.
EQSmodel	The input file for EQS. If omitted, only the first-stage analysis will be conducted.
varphi	Proportion of data to be down-weighted. Default is 0.1.
max.it	Maximum number of iterations for EM. Default is 1000
st	Starting values for EM algorithm. The default is 0 for mean and I for covariance. Alternative, the starting values can be estimated according to MCD.
eqsdata	Data file name used in EQS
eqsweight	File name for weight matrix
EQSpgm	The path to the installed EQS program
serial	The serial no of EQS

Details

This function will run the robust analysis and output results.

Value

If EQSmodel is not supplied

sem	Information for SEM analysis including estimated means, covariance matrix and their sandwich type covariance matrix in the order of mean first and then covariance matrix.
misinfo	Information related to missing data pattern
em	Results from expectation robust algorithm
ascov	Covariance matrix

If EQSmodel is supplied,

sem	Information for SEM analysis including estimated means, covariance matrix and their sandwich type covariance matrix according to the requirement of EQS.

In addition, the following model parameters are from EQS

fit.stat	Fit indices and associated p-values
para	Parameter estimates
eqs	All information from REQS

Author(s)

Ke-Hai Yuan and Zhiyong Zhang

References

Ke-Hai Yuan and Zhiyong Zhang (2011) Robust Structural Equation Modeling with Missing Data and Auxiliary Variables

See Also

rsem.pattern, rsem.emmusig, rsem.Ascov

Examples

## Not run: 
## an example
 ## to use eqs, first load the package semdiag
 library(semdiag)
 data(mardiamv25)
 analysis<-rsem(mardiamv25, c(1,2,4,5), 'eqsinput.eqs')
 
## End(Not run)

rsem documentation built on Aug. 27, 2023, 1:06 a.m.