Bayesian evaluation of informative hypotheses

This book provides the philosophical, statistical and psychological foundation for the evaluation of informed hypotheses. Provides a step-by-step explanation aimed mainly at social scientists, of how to formulate and evaluate a set of informative hypotheses (including references to software) Easily accessed bysocial scientists introducing and elaborating the approach from a philosophical, statistical, and psychological point of view INDICE: A philosophical foundation of null, alternative and informative hypotheses, Jan-Willem Romeijn and Rens van de Schoot.- Famous psychological data sets and hypotheses, Paul Boelen and Herbert Hoijtink.- Sampling the posterior distributions of inequality constrained models, Irene Klugkist and Joris Mulder.- Encompassing priors, Irene Klugkist.- Intrinsic bayes factors, Jim Berger.- Bayes factors without priors, Valen Johnson.- Applications of bayes factors based on differenct prior distributions to classical psychological data sets, Paul Boelen, Floryt van Wesel and Herbert Hoijtink.- The bayes factor versus hypothesis testing using P-values, Susie Bayarri.- The bayes factor versus other model selection criteria, Ming Chen.- Inequality constrained latent classanalysis, Herbert Hoijtink.- Inequality constrained multilevel analysis, Bernet Kato and Paul Boelen.- Inequality constrained analysis of contingency tables, Olav Laudy and Paul Boelen.- A philosopher of sciences view on informed hypotheses, Colin Howson.- A psychologists view on informed hypotheses, Marcel van den Hout and Marleen Rijkeboer.- A statisticians view on informed hypotheses, Jay Myung.

• ISBN: 978-0-387-09611-7
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 364
• Fecha Publicación: 01/12/2008
• Nº Volúmenes: 1
• Idioma: Inglés