Robustness Studies in Covariance Structure Modeling

Jeffrey J. Hoogland and Anne Boomsma
Additional contact information
Jeffrey J. Hoogland: University of Groningen
Anne Boomsma: University of Groningen

Sociological Methods & Research, 1998, vol. 26, issue 3, 329-367

Abstract: In covariance structure modeling, several estimation methods are available. The robustness of an estimator against specific violations of assumptions can be determined empirically by means of a Monte Carlo study. Many such studies in covariance structure analysis have been published, but the conclusions frequently seem to contradict each other. An overview of robustness studies in covariance structure analysis is given, and an attempt is made to generalize findings. Robustness studies are described and distinguished from each other systematically by means of certain characteristics. These characteristics serve as explanatory variables in a meta-analysis concerning the behavior of parameter estimators, standard error estimators, and goodness-of-fit statistics when the model is correctly specified.

Date: 1998
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0049124198026003003 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:somere:v:26:y:1998:i:3:p:329-367

DOI: 10.1177/0049124198026003003

Access Statistics for this article

More articles in Sociological Methods & Research
Bibliographic data for series maintained by SAGE Publications ().