Research Methods and Techniques
Current facets (Pre-Master)
Research in Psychology / Pedagogy and Education
The research activities of the Methods and Techniques section are diverse, and focused on practical application as well as theoretical and fundamental investigation.
We collaborate with colleagues from the social sciences and other disciplines to jointly work on applied research projects, and also offer our expertise on study-design and statistical analysis in an advisory role. The topics of our applied research range from academic performance and its possible predictors, to studies on the influence of marital problems on (mal)adaptation. In addition, it features studies aimed at
- individuals (e.g., single case randomized test designs in a clinical context),
- (large) groups of people (e.g., how to effectively use multimedia in teaching),
- and bodies of scientific literature (e.g., meta-analyses of reading interventions).
Our fundamental research aspires to develop and improve statistical techniques for the study of social phenomena and concepts. Within our own faculty and university this research is used to improve teaching, grading and research. For example, by evaluating different methods for determining students’ real ability from (combinations of) test-scores, and the development of Bayesian multilevel models ideally suited for intensively sampled diary-studies. External collaborations include projects with medical doctors, biologists, teachers and healthcare professionals and have led to such developments as an innovative new analysis approach for the calculation of relative cost-effectiveness of different treatments for borderline personality disorder.
Our department is a hub of advanced statistical expertise, and uses techniques such as Meta-Analysis, Item-Response Theory, Latent Class Modeling, Multilevel Modeling, Structural Equation Modeling, Missing Data Imputation, and Bayesian Statistics. We also employ a variety of statistical software packages, such as SPSS, SAS, Mplus, LatentGold, MLWin, HLM, JAGS, and R, and offer support on the use of these programmes.
Contact: prof. dr. Lidia Arends