Researchers Involved in the Project Presented on this Website:
The project was founded by Herbert Hoijtink in 1994. Around 2000 Irene Klugkist, Olav Laudy and Bernet Kato were added to the project team. Around 2005 the team was further reinforced with Rens van de Schoot, Hennie Boeije, Floryt van Wesel, Carel Peeters, Jan-Willem Romeijn, Joris Mulder and Rebecca Kuiper.
Informative Hypotheses are hypotheses constructed using (in)equality constraints among the parameters of interest. A simple example is three ordered means, Hi: μ1 > μ2 > μ3. Often informative hypothesis paint a more realistic picture of the state of affairs in a population expected by a researcher than the traditional null and alternative hypotheses. Below our work in the area of informative hypotheses is presented. Five topics will be addressed: applications of informative hypotheses in the social, behavioural and other sciences; evaluation of informative hypotheses using hypothesis testing; evaluation of informative hypotheses using the Bayes factor and other information criteria; PhD theses in the area of informative hypotheses; and, software that can be used for the evaluation of informative hypotheses.
Applications of Informative Hypotheses
The papers that are listed here describe applications of informative hypotheses in the social, behavioural and other sciences. These papers illustrate what can be done with informative hypotheses for those that are interested in using them for their own research. Note that software with which informative hypotheses can be evaluated can be found below.
Evaluation of Informative Hypotheses using Hypothesis Testing
The papers that are listed here contain research with respect to the evaluation of informative hypotheses using hypothesis testing.
Evaluation of Informative Hypotheses using the Bayes Factor and Other Information Criteria
The papers that are listed here contain research with respect to the evaluation of informative hypotheses using the Bayes factor and other information criteria.
Tutorial papers
Behavioral and social scientist who want to evaluate informative hypotheses for their own data can find tutorial papers here.
Software
The software to evaluate informative hypotheses can be downloaded here.
PhD theses in the Area of Informative Hypotheses
So far the following theses have addressed the topic of informative hypotheses:
- Irene Klugkist: Inequality constrained normal linear models [File]
- Olav Laudy: Bayesian inequality constrained models for categorical data [File]
- Bernet Kato: Inequality constrained hierarchical models [File]
- Rens van de Schoot: Informative hypotheses. How to move beyond classical null hypothesis testing [File]
- Joris Mulder: Bayesian model selection for constrained multivariate normal linear models [File]
- Floryt van Wesel: Priors and prejudice: Using existing knowledge in social science research [File]
Papers in Dutch
The papers that are listed here are written in Dutch.