MTO Colloquium
Tuesday, November 10, PZ 45 at 12:45h
by Prof. dr. Irene Klugkist (Utrecht University)
‘Updating Bayes factors for informative hypotheses in
replication studies’
In the past decade, several researchers have worked on the
development of a Bayesian model selection approach for the evaluation of
informative hypotheses. An example of such a hypothesis is Hi:
mu1<mu2<mu3<mu4, where each mu represents a population mean and
the ordering expresses a theory based, a priori expected pattern among
these means. In my current research, the goal is to combine evidence from
multiple studies investigating the same informative hypothesis, that is, I
examine the behavior of the Bayes factor, our tool for model selection,
when studies are replicated. Using the binomial model as an example, I
will show some preliminary results using different approaches of
combining information. I like to discuss these results and possible
interpretations as well as implications for users of our methods and
software.