Dr. Sophia Rabe Hesketh

Biography

Sophia Rabe-Hesketh is a distinguished statistician with extensive expertise in multilevel and hierarchical modeling, item response theory, longitudinal data analysis, and handling missing data. She has authored 130 peer-reviewed articles appearing in notable journals such as Psychometrika, Journal of Econometrics, Biometrics, and Journal of the Royal Statistical Society. Rabe-Hesketh is known for developing the GLLAMM framework, a well-regarded modeling approach for multilevel latent variable models, and for creating the gllamm software package to facilitate model estimation. Some of her significant published works include 'Generalized Latent Variable Modeling', co-authored with Anders Skrondal, and various articles focusing on Bayesian methods, model assessments, and the implications of multilevel models in social sciences. She served as the President of the Psychometric Society from 2014 to 2015 and was elected to the National Academy of Education in 2015. As an influential member of the academic community, she has held advisory positions, including on the Design and Analysis Committee of the National Assessment of Educational Progress. Her dedication to teaching and research has made her an esteemed faculty member at the University of California, Berkeley and previously at the Institute of Education, University of London, where she significantly contributed to the field of educational statistics and social research methodologies.

Research Interests

Experience