Stephen Raudenbush

About

Stephen Raudenbush is the Lewis-Sebring Distinguished Service Professor in the Department of Sociology, the College, and the Harris School of Public Policy Studies at the University of Chicago. He holds a B.A., Ed.M., and Ed.D. from Harvard University. His research interests include the sociology of education and quantitative methods, with a focus on statistical models for child and youth development within social settings such as classrooms, schools, and neighborhoods. Raudenbush is best known for developing hierarchical linear models, which have broad applications in the design and analysis of longitudinal and multilevel research. His current work involves studying the development of literacy and math skills in early childhood with implications for instruction, as well as methods for assessing school and classroom quality. He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences, and has received the American Educational Research Association award for Distinguished Contributions to Educational Research.

Research topics

• Computer Science
• Mathematics education
• Psychology
• Artificial Intelligence
• Developmental psychology
• Machine Learning
• Sociology
• Social Science
• Econometrics
• Management science

Selected publications

• Does Schooling Increase or Reduce Social Inequality?

  Annual Review of Sociology · 2015-08-14 · 163 citations

  articleOpen access1st authorCorresponding

  Does experience in school increase or reduce social inequality in skills? Sociologists have long debated this question. Drawing from the counterfactual account of causality, we propose that the impact of going to school on a given skill depends on the quality of the instructional regime a child will experience at school compared with the quality of the instructional regime the child would receive if not at school. Children vary in their benefit from new instruction, and current skill increases t…

  PublisherOA PDFDOI

• Learning About and From a Distribution of Program Impacts Using Multisite Trials

  American Journal of Evaluation · 2015-09-04 · 61 citations

  article1st author

  The present article provides a synthesis of the conceptual and statistical issues involved in using multisite randomized trials to learn about and from a distribution of heterogeneous program impacts across individuals and/or program sites. Learning about such a distribution involves estimating its mean value, detecting and quantifying its variation, and estimating site-specific impacts. Learning from such a distribution involves studying the factors that predict or explain impact variation. Par…

  PublisherDOI

• Using Multisite Experiments to Study Cross-Site Variation in Treatment Effects: A Hybrid Approach With Fixed Intercepts and a Random Treatment Coefficient

  Journal of Research on Educational Effectiveness · 2016-12-29 · 55 citations

  article

  The present article considers a fundamental question in evaluation research: “By how much do program effects vary across sites?” The article first presents a theoretical model of cross-site impact variation and a related estimation model with a random treatment coefficient and fixed site-specific intercepts. This approach eliminates several biases that can arise from unbalanced sample designs for multisite randomized trials. The article then describes how the approach operates, explores its assu…

  PublisherDOI

• Randomized Experiments in Education, with Implications for Multilevel Causal Inference

  Annual Review of Statistics and Its Application · 2020 · 42 citations

  1st authorCorresponding

  Education research has experienced a methodological renaissance over the past two decades, with a new focus on large-scale randomized experiments. This wave of experiments has made education research an even more exciting area for statisticians, unearthing many lessons and challenges in experimental design, causal inference, and statistics more broadly. Importantly, educational research and practice almost always occur in a multilevel setting, which makes the statistics relevant to other fields…

  PublisherOA PDFDOI

• To What Extent Do Student Perceptions of Classroom Quality Predict Teacher Value Added

  2015-09-01 · 39 citations

  other1st authorCorresponding
  PublisherDOI

Recent grants

• NIH Grant R01MH056600

  NIH · $399k · 2001

• Enviromental & Biological Variation and Language Growth

  NIH · $34.1M · 2002–2020

Frequent coauthors

• Robert J. Sampson

  Harvard University

  387 shared

• Felton J. Earls

  374 shared

• Jeanne Brooks‐Gunn

  Columbia University

  347 shared

• J. Douglas Willms

  Learning Partnership

  35 shared

• Anthony S. Bryk

  21 shared

• Sean F. Reardon

  Stanford University

  17 shared

• Jeanne Brooks‐Gunn

  14 shared

• Guanglei Hong

  12 shared

Awards & honors

• American Educational Research Association award for Distingu…
• Member of the National Academy of Sciences
• Member of the American Academy of Arts and Sciences

Similar researchers at University of Chicago

• Linda Waiteh-73
• Neil Brennerh-50
• Terry N. Clarkh-38