Journal
STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL
Volume 21, Issue 1, Pages 149-160Publisher
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/10705511.2013.824793
Keywords
nonnormal data; robust standard errors; Satorra-Bentler scaled chi-square
Ask authors/readers for more resources
Robust corrections to standard errors and test statistics have wide applications in structural equation modeling (SEM). The original SEM development, due to Satorra and Bentler (1988, 1994), was to account for the effect of nonnormality. Muthen (1993) proposed corrections to accompany certain categorical data estimators, such as cat-LS or cat-DWLS. Other applications of robust corrections exist. Despite the diversity of applications, all robust corrections are constructed using the same underlying rationale: They correct for inefficiency of the chosen estimator. The goal of this article is to make the formulas behind all types of robust corrections more intuitive. This is accomplished by building an analogy with similar equations in linear regression and then by reformulating the SEM model as a nonlinear regression model.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available