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Ludtke, Oliver; Robitzsch, Alexander; Kenny, David A.; Trautwein, Ulrich – Psychological Methods, 2013
The social relations model (SRM) is a conceptual, methodological, and analytical approach that is widely used to examine dyadic behaviors and interpersonal perception within groups. This article introduces a general and flexible approach to estimating the parameters of the SRM that is based on Bayesian methods using Markov chain Monte Carlo…
Descriptors: Statistical Analysis, Computation, Interpersonal Relationship, Models
Markon, Kristian E. – Psychological Methods, 2013
Although advances have improved our ability to describe the measurement precision of a test, it often remains challenging to summarize how well a test is performing overall. Reliability, for example, provides an overall summary of measurement precision, but it is sample-specific and might not reflect the potential usefulness of a test if the…
Descriptors: Measures (Individuals), Psychometrics, Statistical Analysis, Bayesian Statistics
Muthen, Bengt; Asparouhov, Tihomir – Psychological Methods, 2012
This rejoinder discusses the general comments on how to use Bayesian structural equation modeling (BSEM) wisely and how to get more people better trained in using Bayesian methods. Responses to specific comments cover how to handle sign switching, nonconvergence and nonidentification, and prior choices in latent variable models. Two new…
Descriptors: Structural Equation Models, Bayesian Statistics, Factor Analysis, Statistical Analysis
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
Vrieze, Scott I. – Psychological Methods, 2012
This article reviews the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) in model selection and the appraisal of psychological theory. The focus is on latent variable models, given their growing use in theory testing and construction. Theoretical statistical results in regression are discussed, and more important…
Descriptors: Factor Analysis, Statistical Analysis, Psychology, Interviews
Vandekerckhove, Joachim; Tuerlinckx, Francis; Lee, Michael D. – Psychological Methods, 2011
Two-choice response times are a common type of data, and much research has been devoted to the development of process models for such data. However, the practical application of these models is notoriously complicated, and flexible methods are largely nonexistent. We combine a popular model for choice response times--the Wiener diffusion…
Descriptors: Reaction Time, Models, Bayesian Statistics, Experimental Psychology
Alcala-Quintana, Rocio; Garcia-Perez, Miguel A. – Psychological Methods, 2004
Variants of adaptive Bayesian procedures for estimating the 5% point on a psychometric function were studied by simulation. Bias and standard error were the criteria to evaluate performance. The results indicated a superiority of (a) uniform priors, (b) model likelihood functions that are odd symmetric about threshold and that have parameter…
Descriptors: Psychometrics, Computation, Error of Measurement, Bayesian Statistics
Klugkist, Irene; Laudy, Olav; Hoijtink, Herbert – Psychological Methods, 2005
Researchers often have one or more theories or expectations with respect to the outcome of their empirical research. When researchers talk about the expected relations between variables if a certain theory is correct, their statements are often in terms of one or more parameters expected to be larger or smaller than one or more other parameters.…
Descriptors: Researchers, Bayesian Statistics, Mathematical Concepts, Statistical Analysis