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Bayesian Evaluation of Informative Hypotheses / edited by Herbert Hoijtink, Irene Klugkist, Paul Boelen
(Statistics for Social and Behavioral Sciences. ISSN:21997365)

Edition 1st ed. 2008.
Publisher (New York, NY : Springer New York : Imprint: Springer)
Year 2008
Language English
Size XII, 361 p : online resource
Authors Hoijtink, Herbert editor
Klugkist, Irene editor
Boelen, Paul editor
SpringerLink (Online service)
Subjects LCSH:Social sciences -- Statistical methods  All Subject Search
FREE:Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
Notes An Introduction to Bayesian Evaluation of Informative Hypotheses -- An Introduction to Bayesian Evaluation of Informative Hypotheses -- Bayesian Evaluation of Informative Hypotheses -- Illustrative Psychological Data and Hypotheses for Bayesian Inequality Constrained Analysis of Variance -- Bayesian Estimation for Inequality Constrained Analysis of Variance -- Encompassing Prior Based Model Selection for Inequality Constrained Analysis of Variance -- An Evaluation of Bayesian Inequality Constrained Analysis of Variance -- A Further Study of Prior Distributions and the Bayes Factor -- Bayes Factors Based on Test Statistics Under Order Restrictions -- Objective Bayes Factors for Informative Hypotheses: “Completing” the Informative Hypothesis and “Splitting” the Bayes Factors -- The Bayes Factor Versus Other Model Selection Criteria for the Selection of Constrained Models -- Bayesian Versus Frequentist Inference -- Beyond Analysis of Variance -- Inequality Constrained Analysis of Covariance -- Inequality Constrained Latent Class Models -- Inequality Constrained Contingency Table Analysis -- Inequality Constrained Multilevel Models -- Evaluations -- A Psychologist’s View on Bayesian Evaluation of Informative Hypotheses -- A Statistician’s View on Bayesian Evaluation of Informative Hypotheses -- A Philosopher’s View on Bayesian Evaluation of Informative Hypotheses
This book presents an alternative for traditional null hypothesis testing. It builds on the idea that researchers usually have more informative research-questions than the "nothing is going on" null hypothesis, or the "something is going on" alternative hypothesis. To be more precise, researchers often express their expectations in terms of expected orderings in parameters, for instance, in group means. This book introduces a novel approach, wherein theories or expectations of empirical researchers are translated into one or more so-called informative hypotheses, i.e., hypotheses imposing inequality constraints on (some of) the model parameters. As a consequence, informative hypotheses are much closer to the actual questions researchers have and therefore make optimal use of the data to provide more informative answers to these questions. A Bayesian approach is used for the evaluation of informative hypotheses and is introduced at a non-technical level in the context of analysis of variance models. Technical aspects of Bayesian evaluation of informative hypotheses are also considered and different approaches are presented by an international group of Bayesian statisticians. Furthermore, applications in a variety of statistical models including among others latent class analysis and multi-level modeling are presented, again at a non-technical level. Finally, the proposed method is evaluated from a psychological, statistical and philosophical point of view. This book contains numerous illustrations, all in the context of psychology. The proposed methodology, however, is equally relevant for research in other social sciences (e.g., sociology or educational sciences), as well as in other disciplines (e.g., medical or economical research). The editors are all affiliated at the faculty of Social Sciences at Utrecht University in the Netherlands. Herbert Hoijtink is a professor in applied Bayesian statistics at the Department of Methodology and Statistics. Irene Klugkist is assistant professor at the same department, and Paul A. Boelen is assistant professor at the Department of Clinical and Health Psychology
HTTP:URL=https://doi.org/10.1007/978-0-387-09612-4
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Springer eBooks 9780387096124
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Classification LCC:HA1-4737
DC23:300,727
ID 4000116849
ISBN 9780387096124

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