Quantitative Psychology - The 86th Annual Meeting of the Psychometric Society, Virtual, 2021

The volume represents presentations given at the 86th annual meeting of the Psychometric Society, held virtually on July 19-23, 2021. About 500 individuals contributed paper presentations, symposiums, poster presentations, pre-conference workshops, keynote presentations, and invited presentations. Since the 77th meeting, Springer has published the conference proceedings volume from this annual meeting to allow presenters to share their work and ideas with the wider research community, while still undergoing a thorough review process. This proceedings covers a diverse set of psychometric topics, including item response theory, Bayesian models, reliability, longitudinal measures, and cognitive diagnostic models.


Marie Wiberg is professor of statistics with a specialty in psychometrics at Umeå University, Sweden. Her research interests include test equating, applied statistics, large-scale assessments and psychometrics in general.

Dylan Molenaar is assistant professor at the department of psychology, University of Amsterdam, the Netherlands. His research interests include item response theory, factor analysis, response time modeling, mixture modeling, modeling of intelligence test data, and modeling of genotype by environmental interactions.

Jorge González is associate professor at the department of statistics, Pontificia Universidad Católica de Chile. His research interests include statistical modeling of social sciences data, particularly in the fields of educational measurement and psychometrics.

Jee-Seon Kim is professor in the department of educational psychology at the University of Wisconsin-Madison. Her research interests include multilevel and hierarchical modeling, longitudinal data analysis, latent variable modeling, and causal inference with clustered observational data.

Heungsun Hwang is professor in the department of psychology at McGill University. His research interests include multivariate statistics, machine learning, functional data analysis, and genetic and neuroimaging data analysis.