000 05098nam a22004575i 4500
001 978-0-387-09612-4
003 DE-He213
005 20161121231206.0
007 cr nn 008mamaa
008 100301s2008 xxu| s |||| 0|eng d
020 _a9780387096124
_9978-0-387-09612-4
024 7 _a10.1007/978-0-387-09612-4
_2doi
050 4 _aQA276-280
072 7 _aJHBC
_2bicssc
072 7 _aSOC027000
_2bisacsh
082 0 4 _a519.5
_223
245 1 0 _aBayesian Evaluation of Informative Hypotheses
_h[electronic resource] /
_cedited by Herbert Hoijtink, Irene Klugkist, Paul A. Boelen.
250 _a1.
264 1 _aNew York, NY :
_bSpringer New York,
_c2008.
300 _bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStatistics for Social and Behavioral Sciences
505 0 _aAn 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.
520 _aThis 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.
650 0 _aStatistics.
650 1 4 _aStatistics.
650 2 4 _aStatistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
700 1 _aHoijtink, Herbert.
_eeditor.
700 1 _aKlugkist, Irene.
_eeditor.
700 1 _aBoelen, Paul A.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387096117
830 0 _aStatistics for Social and Behavioral Sciences
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-387-09612-4
912 _aZDB-2-SMA
950 _aMathematics and Statistics (Springer-11649)
999 _c509903
_d509903