Professional Biography
Wendy Chan is an expert on educational statistics. She seeks to improve statistical models and analysis so research can better inform policy and practice. Her work tries to unpack the intellectual and statistical challenges of generalizing the results of localized randomized trials to larger populations. She began her career in education as a member of Teach for America, where she taught sixth- and eighth-grade mathematics in a large middle school in New York City.
Wendy Chan is an assistant professor of education in the Human Development and Quantitative Methods Division at Penn GSE. Dr. Chan’s research focuses on applied statistical methods to improve generalizations from small studies in education.
Dr. Chan received her Ph.D. in statistics from Northwestern University, where she was a graduate research assistant for the Institute for Policy Research. She began her career in education as a member of Teach for America, where she taught sixth- and eighth-grade mathematics in a large middle school in New York City. Her work has appeared in the Journal of Research on Educational Effectiveness, the Journal of Educational and Behavioral Statistics, Psychological Methods, and Evaluation Review.
Research Interests and Current Projects
Dr. Chan specializes in applied educational statistics, and her research projects and interests are at the leading edge of work on statistics methods in field contexts, including scaling up interventions. Her current projects assess the extent to which generalizations can be made from small studies and they consider the advantages and tradeoffs of different estimation approaches in the presence of limited data. In another project, Dr. Chan considers the impact of violations in model assumptions on the validity of estimates in generalization studies. In this work, she assesses the effectiveness of robust estimation approaches in improving the precision and bias of estimates when core model assumptions are violated. In addition to her work in generalization, Dr. Chan has also worked on research in experimental design and examined corrections to test statistics in the presence of clustering and treatment effect heterogeneity.
Journal Editorial Boards
Journal of Educational and Behavioral Statistics
Editorial Board