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Edwards, Michael C. – Measurement: Interdisciplinary Research and Perspectives, 2013
This author has had the privilege of knowing Professor Maydeu-Olivares for almost a decade and although their paths cross only occasionally, such instances were always enjoyable and enlightening. Edwards states that Maydeu-Olivares' target article for this issue, ("Goodness-of-Fit Assessment of Item Response Theory Models") provides…
Descriptors: Goodness of Fit, Item Response Theory, Models, Factor Analysis
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Drummond, Gordon B.; Vowler, Sarah L. – Advances in Physiology Education, 2012
Most biological scientists conduct experiments to look for effects, and test the results statistically. One of the commonly used test is Student's t test. However, this test concentrates on a very limited question. The authors assume that there is no effect in the experiment, and then estimate the possibility that they could have obtained these…
Descriptors: Statistical Significance, Scientists, Tests, Biology
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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
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MacCallum, Robert C.; Edwards, Michael C.; Cai, Li – Psychological Methods, 2012
Muthen and Asparouhov (2012) have proposed and demonstrated an approach to model specification and estimation in structural equation modeling (SEM) using Bayesian methods. Their contribution builds on previous work in this area by (a) focusing on the translation of conventional SEM models into a Bayesian framework wherein parameters fixed at zero…
Descriptors: Structural Equation Models, Bayesian Statistics, Computation, Expertise
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Sinharay, Sandip; Dorans, Neil J. – Journal of Educational and Behavioral Statistics, 2010
The Mantel-Haenszel (MH) procedure (Mantel and Haenszel) is a popular method for estimating and testing a common two-factor association parameter in a 2 x 2 x K table. Holland and Holland and Thayer described how to use the procedure to detect differential item functioning (DIF) for tests with dichotomously scored items. Wang, Bradlow, Wainer, and…
Descriptors: Test Bias, Statistical Analysis, Computation, Bayesian Statistics