He is also the Lead Psychometrician for ELPA21. His work focuses on the use of latent variable models, particularly item response theory and diagnostic classification models, to support the design of educational, psychological, and health-related assessments. In this breakout session, he will describe the methods used to optimize the ELPA21 screener design, with particular focus on the specification of an early stopping rule to minimize testing burden while ensuring high classification accuracy.