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The article discusses the use of Bayes factors in psychological research for model selection, emphasizing the challenges of computation in Bayesian analysis. It introduces the Savage-Dickey density ratio as a method for estimating Bayes factors efficiently using Markov Chain Monte Carlo (MCMC) sampling, particularly in designs with multiple effect parameters. The authors demonstrate the application of this method in one-sample and one-way ANOVA designs, highlighting its advantages over traditional approache

Author

Ahmed HAMIMES

Language

EN