Psychological Methods

Our mission is to improve psychological science in two ways: by developing research methodology and by contributing novel psychological theory.

Research programme

Our mission is to improve psychological science in two ways: by developing research methodology and by contributing novel psychological theory. Our cross-cutting vision is that these two strands of science are intertwined: Good substantive theories can be represented in mathematical form, and because formalized substantive theories are closely connected to statistical models, developing methodology goes hand in hand with developing theory. The simultaneous development of novel substantive theories and methodologies suited to test them defines the unique and internationally acclaimed focus of our group.

Three research lines

The first research line aims at formalizing psychological theory by using models and techniques that originates in complex system research in the natural sciences. This includes novel theoretical and methodological approaches related to psychometrics. This work inspired the Math Garden project, a web-based practice and monitoring platform (now maintained by the successful spin-off Oefenweb.nl) to collect high frequent data on learning processes. 

The second line concerns a research program on network approaches to psychometrics.  In this program, psychological constructs are viewed as complex networks rather than as latent variables. A particularly successful application of this modeling framework is in the field of psychopathology, where the approach has led to publications in leading journals in the field and is producing significant changes in how researchers think about mental disorders.

The third line concerns mathematical psychology, with a focus on formal models of human cognition. The overarching goal is to restructure the fragmented field of cognitive modeling by adopting Bayesian principles. The line led to the development of JASP, an open-source software package for statistical analyses, with an emphasis on Bayesian methods (jasp-stats.org). 

Published by  PRI

10 April 2018