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Wills, Andy J.; Pothos, Emmanuel M. – Psychological Bulletin, 2012
Vanpaemel and Lee (2012) argued, and we agree, that the comparison of formal models can be facilitated by Bayesian methods. However, Bayesian methods neither precede nor supplant our proposals (Wills & Pothos, 2012), as Bayesian methods can be applied both to our proposals and to their polar opposites. Furthermore, the use of Bayesian methods to…
Descriptors: Classification, Bayesian Statistics, Models, Comparative Analysis
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Lubke, Gitta – Measurement: Interdisciplinary Research and Perspectives, 2012
Von Davier et al. (this issue) describe two analyses that aim at determining whether the constructs measured with a number of observed items are categorical or continuous in nature. The issue of types versus traits has a long history and is relevant in many areas of behavioral research, including personality research, as emphasized by von Davier…
Descriptors: Models, Classification, Multivariate Analysis, Statistical Analysis
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Griffiths, Thomas L.; Chater, Nick; Norris, Dennis; Pouget, Alexandre – Psychological Bulletin, 2012
Bowers and Davis (2012) criticize Bayesian modelers for telling "just so" stories about cognition and neuroscience. Their criticisms are weakened by not giving an accurate characterization of the motivation behind Bayesian modeling or the ways in which Bayesian models are used and by not evaluating this theoretical framework against specific…
Descriptors: Bayesian Statistics, Psychology, Brain, Models
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Rindskopf, David – Psychological Methods, 2012
Muthen and Asparouhov (2012) made a strong case for the advantages of Bayesian methodology in factor analysis and structural equation models. I show additional extensions and adaptations of their methods and show how non-Bayesians can take advantage of many (though not all) of these advantages by using interval restrictions on parameters. By…
Descriptors: Structural Equation Models, Bayesian Statistics, Factor Analysis, Computation