Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures.

作者: Karin Schermelleh-Engel , Helfried Moosbrugger , Hans Müller

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摘要: For structural equation models, a huge variety of fit indices has been developed. These indices, however, can point to conflicting conclusions about the extent which model actually matches observed data. The present article provides some guidelines that should help applied researchers evaluate adequacy given model. First, as goodness-of-fit measures depend on method used for parameter estimation, maximum likelihood (ML) and weighted least squares (WLS) methods are introduced in context modeling. Then, most common discussed recommendations practitioners given. Finally, we generated an artificial data set according "true" analyzed two misspecified correctly specified models examples poor fit, adequate good fit.

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