Stephen Raudenbush is the Lewis-Sebring Distinguished Service Professor in the Department of Sociology, the College and the Harris School of Public Policy Studies.
He is interested in statistical models for child and youth development within social settings such as classrooms, schools, and neighborhoods. He is best known for his work developing hierarchical linear models, with broad applications in the design and analysis of longitudinal and multilevel research. he is currently studying the development of literacy and math skills in early childhood with implications for instruction; and methods for assessing school and classroom quality. He is a member of the National Academy of Sciences, the American Academy of Arts and Sciences the recipient of the American Educational Research Association award for Distinguished Contributions to Educational Research.
Recent Research / Recent Publications
Nomi, T., Raudenbush, S.W., and Smith, J. (2021). Effects of Double-Dose Algebra on College Persistence and Degree Attainment to appear in the Proceeding of the National Academy of Sciences. 118(27), dco10.1073/pnas.2019030118.
Raudenbush, S.W., Hernandez, M., Goldin-Meadow, S., Carrazza, C., Foley, A., Leslie, D., Sorkin, J.E., and Levine, S. (2020). Longitudinally Adaptive Assessment and Instruction Increase Numerical Skills of Preschool Children. Proceedings of the National Academy of Sciences, vol. 117, no. 45, 27945–27953.
Silvey, C., Demir-Lira, Ö.,E., Goldin-Meadow, S., and Raudenbush, S.W., (2021). Effects of time-varying parent input on child language outcomes differ for vocabulary and syntax. Psychological Science, Vol. 32(4) 536–548.
Raudenbush, S.W., (2020). Scaling Up Experiments to Reduce Educational Inequality. In A.J. Oliver (Ed.). Behavioural Public Policy. Cambridge: Cambridge University.
Raudenbush, S.W., Schwartz, D., (2020). Randomized experiments in education, with implications for multilevel causal inference. Annual Review of Statistics and Its Application. 7:1, 177-208.