Elizabeth Tipton
Professor of Statistics and Data Science | Professor of Education and Social Policy (by courtesy)
IPR Fellow and Co-Chair of IPR’s Program on Methods for Policy Research | Co-Director of the STEPP Center
PhD, Statistics; Certificate in Education Science, Northwestern University, 2011
Statistician Elizabeth Tipton joined the Northwestern faculty in 2018, after previously being on the faculty at Teachers College, Columbia University (2011–18). Her research focuses on the design and analysis of field experiments, particularly on their external validity and on how to make causal generalizations from them. She is developing methods and tools to improve the generalizability of large, randomized trials, especially in education and psychology. Her research in meta-analysis—the combination of results across many smaller trials—examines modeling and adjusting for dependence between effect sizes. Additionally, in a new line of research she has begun studying ways to improve the mobilization of statistical information in decision making, e.g., through improved data visualizations and data summaries.
Tipton’s research has been published in the Journal of Educational and Behavioral Statistics, Statistics in Medicine, Psychological Methods, Evaluation Review, and Journal of Research on Educational Effectiveness, among others. Her work has been supported by the National Science Foundation, Institute for Education Sciences, Spencer Foundation, and Raikes Foundation.
Tipton is an elected member of the National Academy of Education and an elected fellow of both the American Statistical Association and the American Educational Research Association. She has served as President of the Society for Research on Educational Effectiveness and Chair of the Social Statistics Section of the American Statistical Association and was a member of the National Academies committee on The Future of Education Research at IES.
Current Research
Generalization and Heterogeneity. For over a decade, Tipton has focused a line of research on improved causal research designs that account for variation in treatment effects. Recently, this has included calls for improved understandings of heterogeneity in randomized trials and in meta-analysis, as well as the development of methods for improved trial designs. She developed and maintains The Generalizer, a free webtool for developing sampling and recruitment plans for randomized trials in K-12 education and for assessing the generalizability of results of a study to different policy relevant populations.
Meta-Analysis. With former IPR graduate research assistant James Pustejovsky (now at the University of Wisconsin–Madison), Tipton is continuing the development of small-sample methods for improved hypothesis testing using Cluster Robust Variance Estimation (CRVE). CRVE is used when there are multiple effect sizes per study in a meta-analysis, and these recent innovations include new working models for implementation. Additionally, Tipton is co-teaching a one-week workshop on introductory meta-analysis methods (MMARI), supported by the National Science Foundation.
Generalization and Heterogeneity. For over a decade, Tipton has focused a line of research on improved causal research designs that account for variation in treatment effects. Recently, this has included calls for improved understandings of heterogeneity in randomized trials and in meta-analysis, as well as the development of methods for improved trial designs.
Knowledge Mobilization. With her former student, Katie Fitzgerald (now at Villanova University), Tipton has been developing and testing new approaches to conveying statistical and research findings to education decision makers. This includes the development of a knowledge mobilization framework, as well as new data visualizations. These data visualizations will be further tested and refined as part of a new grant from the Institute of Education Sciences.
Selected Publications
Tipton, E., and M. Mamakos. 2025. Designing randomized experiments to predict unit-specific treatment effects. Statistics and Public Policy 12(1): 2505485.
Fitzgerald, K., D. Khella, A. Charles, and E. Tipton. 2025. Meta-analytic rain cloud plots: Improving evidence communication through data visualization design principles. Research Synthesis Methods 16(2): 364–82.
Spake, R., E. Jackson, J. Bullock, E. Gardner, E. Tipton, M. Grainger, and C. Doncaster. 2025. Precision ecology for targeted conservation action. Nature Ecology and Evolution 9(7): 1102–11.
Fitzgerald, K., and E. Tipton. 2025. Using extant data to improve estimation of the standardized mean difference. Journal of Educational and Behavioral Statistics 50(1): 128–48.
Fitzgerald, K., and E. Tipton. 2024. A knowledge mobilization framework: Toward evidence-based statistical communication practices in education research. Journal of Research on Educational Effectiveness 17(3): 540–60.
Hou, Z., and E. Tipton. 2024. Enhancing recall in automated record screening: A resampling algorithm. Research Synthesis Methods 15(3): 372–83.
Pustejovsky, J., and E. Tipton. 2022. Meta-analysis with robust variance estimation: Expanding the range of working models. Prevention Science 23: 425–38.
Tipton, E. 2022. Sample selection in randomized trials with multiple target populations. American Journal of Evaluation 43(1): 70–89.
Bryan, C., E. Tipton, and D. Yeager. 2021. Behavioral science is unlikely to change the world without a heterogeneity revolution. Nature Human Behavior 5: 980–89.
Tipton, E. 2021. Beyond the ATE: Designing randomized trials to understand treatment effect heterogeneity. Journal of the Royal Statistics Society: Series A 184(2): 504–21.
Tipton, E., J. Spybrook, K. Fitzgerald, Q. Wang, and C. Davidson. 2021. Towards a system of evidence for all: Current practices and future opportunities in 37 randomized trials. Educational Researcher 50(3): 145–56.
