Researchers in psychology have specific expectations about their theories. These are called informative hypothesis because they contain information about reality. Note that these hypotheses are not necessarily the same as the traditional null and alternative hypothesis. Many researchers use traditional null-hypothesis testing to evaluate informative hypotheses. However, this can be problematic, as will become clear in this article.

We offer an innovative solution to evaluate informed hypotheses based on Bayesian Model Selection. The method is introduced in non-statistical terms and its utility is illustrated by applying it to examples from occupational health psychology.

Van de Schoot, R., Hoijtink, H., & Doosje, S. (2009). Rechtstreeks verwachtingen evalueren of de nulhypothese toetsen? Nulhypothesetoetsing versus Bayesiaanse modelselectie. [Directly evaluating expectations or testing the null hypothesis? Null hypothesis testing versus Bayesian model selection]. De Psycholoog, 4, 196-203. http://dx.doi.org/10.2139/ssrn.1919023

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Herbert Hoijtink
Professor Applied Bayesian Statistics
Herbert's main research interest is the evaluation of Informative Hypotheses. These are hypotheses constructed using (in)equality constraints among the parameters of interest.
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