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de Rooij, Mark; Schouteden, Martijn – Multivariate Behavioral Research, 2012
Maximum likelihood estimation of mixed effect baseline category logit models for multinomial longitudinal data can be prohibitive due to the integral dimension of the random effects distribution. We propose to use multidimensional unfolding methodology to reduce the dimensionality of the problem. As a by-product, readily interpretable graphical…
Descriptors: Statistical Analysis, Longitudinal Studies, Data, Models
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Lombardi, Luigi; Pastore, Massimiliano – Multivariate Behavioral Research, 2012
In many psychological questionnaires the need to analyze empirical data raises the fundamental problem of possible fake or fraudulent observations in the data. This aspect is particularly relevant for researchers working on sensitive topics such as, for example, risky sexual behaviors and drug addictions. Our contribution presents a new…
Descriptors: Deception, Measures (Individuals), Sampling, Structural Equation Models
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Savalei, Victoria; Yuan, Ke-Hai – Multivariate Behavioral Research, 2009
Evaluating the fit of a structural equation model via bootstrap requires a transformation of the data so that the null hypothesis holds exactly in the sample. For complete data, such a transformation was proposed by Beran and Srivastava (1985) for general covariance structure models and applied to structural equation modeling by Bollen and Stine…
Descriptors: Statistical Inference, Goodness of Fit, Structural Equation Models, Transformations (Mathematics)