Sophia Rabe-Hesketh

Sophia Rabe-Hesketh is a statistician whose research interests include multilevel/hierarchical modeling, item response theory, longitudinal data analysis, and missing data. She has over 130 peer-reviewed articles in over 70 different journals including PsychometrikaJournal of EconometricsBiometricsJournal of the Royal Statistical Society, Series A, with an h-index of 74 in Google Scholar. She has developed a modeling framework for a wide range of multilevel and latent variable models called GLLAMM (Generalized Linear Latent and Mixed Modeling) and written a publicly available software package called gllamm (http://www.gllamm.org/(link is external)) to estimate these models. The theory of these models is published in Generalized Latent Variable Modeling(link is external), co-authored with Anders Skrondal. Since 2002, her gllamm software has been used in over 1000 peer-reviewed papers in over 700 different journals by researchers in education, sociology, political science, economics, medicine, and statistics.

Sophia Rabe-Hesketh was elected to the National Academy of Education in 2015 and was President of the Psychometric Society in 2014-2015. She is a member of the Design and Analysis Committee for the National Assessment of Educational Progress (NAEP). She has been Associate Editor for Psychometrika among others and served on Editorial Boards for Journal of Educational and Behavioral StatisticsPsychological Methods, and others.

Sophia Rabe-Hesketh is also a member of the Interdepartmental Group in Biostatistics(link is external) at the University of California, Berkeley. She was previously Professor of Social Statistics at the Institute of Education, University of London.

See ISI Web of Science(link is external) and Google scholar(link is external) for lists of publications and citations.

Degree(s)

PhD, King's College, University of London, Theoretical Physics

Curriculum Vitae

Contact

Office #4228

School of Education
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UC Berkeley
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Berkeley, CA 94720-1670