Bayesian Evaluation of Informative Hypotheses
Herbert Hoijtink, Irene Klugkist, Paul Boelen
Springer Science & Business Media, Sep 8, 2008 - Social Science - 361 pages
This book provides an overview of the developments in the area of Bayesian evaluation of informative hypotheses that took place since the publication of the ?rst paper on this topic in 2001 [Hoijtink, H. Con?rmatory latent class analysis, model selection using Bayes factors and (pseudo) likelihood ratio statistics. Multivariate Behavioral Research, 36, 563–588]. The current state of a?airs was presented and discussed by the authors of this book during a workshop in Utrecht in June 2007. Here we would like to thank all authors for their participation, ideas, and contributions. We would also like to thank Sophie van der Zee for her editorial e?orts during the construction of this book. Another word of thanks is due to John Kimmel of Springer for his con?dence in the editors and authors. Finally, we would like to thank the Netherlands Organization for Scienti?c Research (NWO) whose VICI grant (453-05-002) awarded to the ?rst author enabled the organization of the workshop, the writing of this book, and continuation of the research with respect to Bayesian evaluation of informative hypotheses.
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Part II A Further Study of Prior Distributions and theBayes Factor
Part III Beyond Analysis of Variance
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alternative amnesia analysis of variance ANOVA model Bayes factor Bayesian approach Bayesian inference Bayesian model selection Bayesian statistical burn-in Chapter compute constrained hypotheses constrained model covariate credibility intervals dataset deﬁned denote density depression DID-patients diﬀerent discussed dissociative identity disorder emotional reactivity encompassing prior approach equal estimates evaluation example feedback ﬁnd ﬁrst ﬁt frequentist inference function gender Gibbs sampler Hoijtink Huntjens hypothesis testing inﬂuence informative hypotheses iterations Journal latent class analysis latent class models linear log-linear main eﬀects marginal likelihood measure methods model parameters NHST normal distribution null hypothesis observed data obtained p-value parameter space posterior distribution posterior mean posterior model probabilities posterior probabilities predictive prior distribution prior probability procedure Psychological sample satisﬁed scientiﬁc Section service level set of hypotheses signiﬁcant Simulators speciﬁcation standard deviation Table theories True amnesiacs unconstrained hypothesis values variable µ amn µamn µcon µpat µsim