Erik-Jan van Kesteren

photo_vankesterenMethodolgy & Statistics
Faculty of Social Sciences
Utrecht University

Email Erik-Jan van Kesteren
Phone: +31 302534053
Academic webpage Erik-Jan van Kesteren

On January 29th 2021 Erik-Jan van Kesteren defended his thesis (cum laude) Structural Equations with Latent Variables: Computational Solutions for Modern Data Problems at the Utrecht University.

Summary
Structural Equation Modeling (SEM) is a flexible and popular method for data analysis in the social and behavioral sciences. SEM is particularly suitable for research situations in which concepts cannot be measured directly, or where the instruments used for measurement are error-prone. Examples are “trust” or “well-being” — concepts which are indirectly measured with questionnaires. But the modern data landscape is changing, and SEM is reaching its limits: Classic survey and experimental research is being supplemented (and sometimes even supplanted) by research using measurements from register data, wearable sensors, images, internet databases, genetic sequencing, advanced brain imaging techniques, and more. The SEM method is not always available for these, but the problems of fallible measurement do not disappear in this modern data landscape, and many research questions using this data still involve causal relations between latent constructs. Analyses using SEM are therefore of great value for research with such new measuring instruments. Thus, the goal of this dissertation is to make SEM analyses available to a wider range of these modern datasets. To this end, I develop several solutions to problems encountered in the application of SEM to such data.

Supervisors
Dr Daniel Oberski & Prof. Irene Klugkist

Financed by
NWO Research Talent Grant

Period
1 September 2017 – 29 January 2021