Robustness studies in covariance structure modeling - An overview and a meta-analysisHoogland, J. J. & Boomsma, A., Feb-1998, In : Sociological Methods & Research. 26, 3, p. 329-367 39 p.
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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.
|Number of pages||39|
|Journal||Sociological Methods & Research|
|Publication status||Published - Feb-1998|
- CONFIRMATORY FACTOR-ANALYSIS, MAXIMUM-LIKELIHOOD, LATENT-VARIABLES, EQUATION MODELS, TEST STATISTICS, MEASUREMENT ERROR, LIKERT VARIABLES, SAMPLING ERROR, ESTIMATORS, METHODOLOGIES