Modern Approaches in Measurement

An atypical course in latent variable measurement that combines psychometric modeling with unsupervised machine learning.

The course provides students with the software skills and theoretical knowledge required to apply latent construct measurement techniques in R. The course assumes a working knowledge of R, linear regression, and basic probability. Continuous and categorical latent variables, dimensionality reduction, clustering, finite mixture, and diagnostic classification models are covered. The course focuses on cross-sectional applications of measurement techniques, with examples drawn from education, psychology, and social science.