David Kaplan

Hilldale Professor and Patricia Busk Professor of Quantitative Methods, Quantitative Methods Area


(608) 262-0836

1082B Educational Sciences

1025 West Johnson Street

Madison, WI 53706-1706

Kaplan, David

Download CV   WEBSITE: Bayesian Methods for Education Research  

David Kaplan is Hilldale Professor and Patricia Busk Professor of Quantitative Methods in the Department of Educational Psychology at the University of Wisconsin – Madison. Dr. Kaplan holds affiliate appointments in the University of Wisconsin’s Department of Population Health Sciences and the Center for Demography and Ecology. Dr. Kaplan’s program of research focuses on the development of Bayesian statistical methods for education research. His work on these topics is directed toward applications to large-scale cross-sectional and longitudinal survey designs. Dr. Kaplan is an elected member of the National Academy of Education and served as the chair of its Research Advisory Committee. Kaplan is a recipient of the Samuel J. Messick Distinguished Scientific Contributions Award from the American Psychological Association (Division 5); a past-President of the Society for Multivariate Experimental Psychology; a fellow of the American Psychological Association (Division 5); a recipient of the Alexander Von Humboldt Research Award; and a fellow of the Leibniz Institute for Educational Trajectories; and was a Jeanne Griffith Fellow at the National Center for Education Statistics. Dr. Kaplan received his Ph.D. in education from UCLA in 1987.


  • PhD Education, University of California - Los Angeles, 1987
  • MA Education, University of California - Los Angeles, 1983
  • BA Psychology, California State University - Northridge, 1978

Select Publications

  • Kaplan, D., & Harra, K. (2024). A Bayesian workflow for the analysis and reporting of international large-scale assessments: A case study using the OECD Teaching and Learning International Survey. Large-Scale Assessments in Education https://doi.org/10.1186/s40536- 023-00189-1.
  • Larson, C., Kaplan, D., Girolamo, T., Kover, S. T., & Eigsti, I.-M. (2023). A Bayesian statistics tutorial for clinical research: Prior distributions and meaningful results for small clinical samples. Journal of Clinical Psychology https://doi.org/10.1002/jclp.23570.
  • Kaplan, D. (2023). Bayesian Statistics for the Social Sciences (2nd Edition) New York: Guilford Press.
  • Harra, K., & Kaplan, D. (2023). On the performance of horseshoe priors for inducing sparsity in structural equation models. Structural Equation Modeling https://doi.org/10.1080/10705511.2023.2280895.
  • Kaplan, D., Chen, J., Lyu, W., & Yavuz, S. (2023). Bayesian historical borrowing with longitudinal large-scale assessments. Large-Scale Assessments in Education DOI.
  • Kaplan, D., Chen, J., Yavuz, S., & Lyu, W. (2022). Bayesian dynamic borrowing of historical information with applications to the analysis of large-scale assessments. Psychometrika https://doi.org/10.1007/s11336-022-09869-3, Download Publication.
  • Kaplan, D. (2021). On the quantification of model uncertainty: A Bayesian perspective. Psychometrika, 86, 215-238. DOI: 10.1007/s11336-021-09754-5, Download Publication.
  • Kaplan, D., & Huang, M. (2021). Bayesian probabilistic forecasting with large-scale educational trend data: A case study using NAEP. Large-Scale Assessments in Education, 9 Online Publication/Abstract, Download Publication.
  • Kaplan, D., & Yavuz, S. (2019). An approach to addressing multiple imputation model uncertainty using Bayesian model averaging. Multivariate Behavioral Research Online Publication/Abstract.
  • Kaplan, D., & Su, D. (2018). On imputation for planned missing data in context questionnaires using plausible values: A comparison of three designs. Large-Scale Assessments in Education Online Publication/Abstract.

Select Presentations

  • Kaplan, D., Chen, J., Yavuz, S., & Lyu, W. (2022, July). Borrowing Historical Information for the Analysis of Large-Scale Assessments. Paper presented at the meeting of the International Society for Bayesian Analysis, Montreal, Canada.
  • Kaplan, D. (2021, October). Bayesian Statistics for Beginners. presented at the Presented to the Deutsches Jugendinstitut, Munich, Germany.
  • Kaplan, D. (2021, October). A Gentle Introduction to Bayes. presented at the Institute of Sociology, University of Jena, Jena, Germany.
  • Kaplan, D. (2021, July). Bayesian Dynamic Borrowing for Single and Multilevel Models. presented at the State-of-the-art paper presented (virtually) to the European Association of Methodology, Valencia, Spain.
  • Kaplan, D. (2019). An Approach to Addressing Multiple Imputation Model Uncertainty Using Bayesian Model Averaging. Paper presented at the DAGStat 2019 (Deutsche Arbeitsgemeinschaft Statisk), Munich, Germany.
  • Kaplan, D. (2019, November). Recent Developments and Future Directions in Bayesian Model Averaging. Lecture presented at the Donald O. Hebb Lecture Series, Montreal, Canada.
  • Kaplan, D. (2019, October). Quantifying Uncertainty in Models and Methods: Overview and Recent Developments in Bayesian Model Averaging. Talk presented at the Department of Psychology, Fordham University, New York City, NY.
  • Kaplan, D. (2019, October). The Bayesian Revolution and Why You Should Care. Lecture presented at the The 2019 Anastasi Lecture, New York City, NY.
  • Kaplan, D. (2019, October). Quantifying Uncertainty in Models and Methods: Overview and Recent Developments in Bayesian Model Averaging. Lecture presented at the Distinguished Lecture, Belval, Luxembourg.
  • Kaplan, D. (2019, January). Quantifying Uncertainty in Models and Methods: A Bayesian Perspective. Talk presented at the Luxembourg Institute for Socio-Economic Research, Belval, Luxembourg.

Select Awards and Honors

  • President, Psychometric Society, (2023-2024)
  • International Guest Professor, Institut für Bildungswissenshaft, Universität Heidelberg, (January - June, 2023)
  • Max Kade Visiting Professor, University of Heidelberg, (2021–2022)
  • Hilldale Award in the Social Sciences, University of Wisconsin - Madison, (2019–2020)
  • Research Fellow, DIPF - Leibniz Institute for Research and Information in Education, (2016–2020)
  • Samuel J. Messick Award for Distinguished Scientific Contributions, APA, Division 5, 2018
  • President, Society of Multivariate Experimental Psychology, (2017–2018)
  • Johann Baptist von Spix International Visiting Professor, Department of Statistics and Econometrics, University of Bamberg, 2018
  • Faculty Distinguished Achievement Award, School of Education, University of Wisconsin – Madison, 2016
  • Humboldt Research Award, Alexander von Humboldt Foundation, (2015–2016)