swMATH ID: 
6771

Software Authors: 
Yuan, KeHai; Zhang, Zhiyong

Description: 
Robust structural equation modeling with missing data and auxiliary variables
The paper develops a twostage robust procedure for structural equation modeling (SEM) and an R package rsem to facilitate the use of the procedure by applied researchers. In the first stage, Mestimates of the saturated mean vector and covariance matrix of all variables are obtained. Those corresponding to the substantive variables are then fitted to the structural model in the second stage. A sandwichtype covariance matrix is used to obtain consistent standard errors (SE) of the structural parameter estimates. Rescaled, adjusted as well as corrected and Fstatistics are proposed for overall model evaluation. Using R and EQS, the R package rsem combines the two stages and generates all the test statistics and consistent SEs. Following the robust analysis, multiple model fit indices and standardized solutions are provided in the corresponding output of EQS. An example with open/closed book examination data illustrates the proper use of the package. The method is further applied to the analysis of a data set from the National Longitudinal Survey of Youth 1997 cohort, and results show that the developed procedure not only gives a better endorsement of the substantive models but also yields estimates with uniformly smaller standard errors than the normaldistributionbased maximum likelihood. 
Homepage: 
http://cran.rproject.org/web/packages/rsem/index.html

Source Code: 
https://github.com/cran/rsem

Dependencies: 
R 
Keywords: 
auxiliary variables;
estimating equation;
missing at random;
R package rsem;
sandwichtype covariance matrix

Related Software: 
WinBUGS;
WRS2;
bootstrap;
robustbase;
REQS;
EQS;
sem;
R

Cited in: 
4 Publications
