Illustrating Bayesian Evaluation of Informative Hypotheses for Regression Models

نویسندگان

  • Anouck Kluytmans
  • Rens van de Schoot
  • Joris Mulder
  • Herbert Hoijtink
چکیده

In the present article we illustrate a Bayesian method of evaluating informative hypotheses for regression models. Our main aim is to make this method accessible to psychological researchers without a mathematical or Bayesian background. The use of informative hypotheses is illustrated using two datasets from psychological research. In addition, we analyze generated datasets with manipulated differences in effect size to investigate how Bayesian hypothesis evaluation performs when the magnitude of an effect changes. After reading this article the reader is able to evaluate his or her own informative hypotheses.

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عنوان ژورنال:

دوره 3  شماره 

صفحات  -

تاریخ انتشار 2012