Bayesian Evaluation of Informative Hypotheses Illustrated with an Application to Dynamical Modelling
Even after decades of critique, null-hypothesis significance testing is still the dominant research paradigm in the behavioural and social sciences. This is perhaps explained by the fact that the focus has been too much on critique and too little on viable, broadly applicable alternatives, that are implemented in user friendly software packages. In this presentation, first of all, a resume of the main critique of null-hypothesis significance testing will be given. Subsequently, an alternative, Bayesian evaluation of informative hypotheses, will be introduced. This entails using the Bayes factor to evaluate hypotheses representing (competing) expectations researchers have with respect to the state of affairs in their population of interest. This approach will be illustrated using a dynamical modelling example.
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