Chair at Utrecht University: 

Methods and techniques for the social and behavioural sciences - Started October 2015

Inaugural lecture: February 10, 2017. Title: Small step or giant leap? Op de weg naar transparante (subjectieve) wetenschap ("Towards transparent (subjective) science"). Full text

Member of the consortium: Prompted Rationality: Roadmaps to a New Public Policy for Promoting Autonomous Choice and Societal Benefits.

Chair at University of Twente (from Jan 2015 - Dec 2017):

Bayesian modelling using informative priors

Key publications on the use of informative priors:

1. Ni, H., Groenwold, R.H.H., Nielen, M., Klugkist, I. (2018). Prediction models for clustered data with informative priors for the random effects: a simulation study. BMC Medical Research Methodology.
2. Rietbergen, C., Groenwold, R.H.H., Hoijtink, H.J.A., Moons, K.G.M., Klugkist, I. (in press). Expert Elicitation of Study Weights for Bayesian Analysis and Meta-Analysis. Journal of Mixed Methods Research, DOI: 10.1177/1558689814553850.
3. Rietbergen, C.,Klugkist, I., Janssen, K.J.M., Moons, K.G.M., Hoijtink, H. (2011). Incorporation of Historical Data in the Analysis of Randomized Therapeutic Trials. Contemporary Clinical Trials, 32, 848-855.

VIDI project:

A different angle: new tools for circular data (website)

Started November 2013

Key publications on circular data analysis

1. Cremers, J. Mulder, K. T., Klugkist, I. (2018). Circular interpretation of regression coefficients. British Journal of Mathematical and Statistical Psychology, 71(1), 75-95.
2. Mulder, K. T. & Klugkist, I. (2017). Bayesian estimation and hypothesis tests for a circular Generalized Linear Model. Journal of Mathematical Psychology, 80, 4-14.
3. Baayen, C.,Klugkist, I. (2014). Evaluating order-constrained hypotheses for circular data from a between-within subjects design. Psychological Methods, 19, 398-408.

PhD-thesis:

Inequality Constrained Normal Linear Models

Defence: February 11th, 2005 - cum laude

Key publications on informative hypothesis:

1. Klugkist, I. and Hoijtink, H. (2007). The Bayes Factor for Inequality and About Equality Constrained Models. Computational Statistics and Data Analysis, 51, 6367-6379.
2. Klugkist, I., Laudy, O. and Hoijtink, H. (2005). Inequality Constrained Analysis Of Variance: A Bayesian Approach. Psychological Methods, 10, 477-493.

Book:

Hoijtink, H., Klugkist, I. and Boelen, P.A., eds. (2008). Bayesian Evaluation of Informative Hypotheses. New York: Springer.

PhD-students:

1. Joris Mulder (December 3rd, 2010) - cum laude
2. Floryt van Wesel (July 1st, 2011)
3. Charlotte Rietbergen (February, 2016)
4. Leonie van Grootel (May 2018)
5. Haifang Ni (2018)
6. Jolien Cremers (2018)
7. Kees Mulder (2018)
8. Fayette Klaassen (2019)
9. Karlijn Soppe (2021)
10. Marieke Westeneng den Otter (2021)
11. Erik-Jan van Kesteren (2021)
12. Hidde Leplaa (2023)