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van de Schoot, Rens; Hoijtink, Herbert; Dekovic, Maja – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Researchers often have expectations that can be expressed in the form of inequality constraints among the parameters of a structural equation model. It is currently not possible to test these so-called informative hypotheses in structural equation modeling software. We offer a solution to this problem using M"plus." The hypotheses are…
Descriptors: Structural Equation Models, Computer Software, Hypothesis Testing, Statistical Analysis
Saris, Willem E.; Satorra, Albert; van der Veld, William M. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Assessing the correctness of a structural equation model is essential to avoid drawing incorrect conclusions from empirical research. In the past, the chi-square test was recommended for assessing the correctness of the model but this test has been criticized because of its sensitivity to sample size. As a reaction, an abundance of fit indexes…
Descriptors: Structural Equation Models, Validity, Goodness of Fit, Evaluation Methods
Cheung, Mike W. -L. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Confidence intervals (CIs) for parameters are usually constructed based on the estimated standard errors. These are known as Wald CIs. This article argues that likelihood-based CIs (CIs based on likelihood ratio statistics) are often preferred to Wald CIs. It shows how the likelihood-based CIs and the Wald CIs for many statistics and psychometric…
Descriptors: Intervals, Structural Equation Models, Simulation, Correlation

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