Robust Structural Equation Models: Implications for Developmental Psychology
Child DevelopmentPublished 1 February 1987
G. J. Huba, Lisa L. Harlow
Citations110
SJR quartileQ1
SJR score2.19
SNIP2.13
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Abstract
HUBA, GEORGE J., and HARLOW, LISA L. Robust Structural Equation Models: Implications for Developmental Psychology. CHILD DEVELOPMENT, 1987, 58, 147-166. Advances in structural equation modeling techniques have made it possible to test models in data that are not normally distributed. This can lead to more realistic model testing in developmental psychology. Several alternate techniques are illustrated in structural equation models here in order to compare the results that are obtained. Maximum-likelihood and generalized least-squares estimators for normally distributed data are compared with Browne's asymptotically distribution-free technique for continuous nonnormally distributed data and Muthen's estimator for dichotomous indicators. While different critical ratios are found for some parameters estimated in models, the results are generally comparable so long as one does not consider absolute fit to be a critical factor in accepting a causal model as a good one.
Keywords
Computer ScienceDecision SciencesMathematics
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