David Kaplan

Professor

david.kaplan@wisc.edu

(608) 262-0836

1082B Educational Sciences
1025 West Johnson St.
Madison, WI 53706-1706

Website: Bayesian Methods for Education Research

Curriculum Vitae

Personal Biography

David Kaplan is the 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 serves at the Chair of its Research Advisory Committee; 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; an Honorary Research Fellow in the Department of Education at the University of Oxford., a fellow of the Leibniz Institute for Educational Research and Information and 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.

Research Interests

My current program of research focuses on the development of Bayesian methods applied to a wide range of education research settings. My specific interests include: Bayesian model averaging; objective versus subjective Bayesian modeling; and Bayesian approaches to problems in large-scale survey methodology. My collaborative research involves applications of advanced quantitative methodologies to substantive and methodological problems in international large-scale assessments in education. I have been actively involved in the OECD Program for International Student Assessment (PISA) where I served on its Technical Advisory Group from 2005-2009 and its Questionnaire Expert Group from 2004-present where I served as the Chair of the Questionnaire Expert Group for PISA 2015 and remain a member of the Questionnaire Expert Group for PISA 2018. I also sit on the Questionnaire Expert Group for the OECD Teaching and Learning International Survey (TALIS) as well as the Design and Analysis Committee and the Questionnaire Standing Committee for the National Assessment of Educational Progress (NAEP).

Teaching Interests

Structural equation modeling, Bayesian statistical methods.

Selected Grants and Sponsorships

  • 2019 – 2022  – Amount: $802,314.  ” Bayesian dynamic borrowing: A method for utilizing historical data in education research” Awarded by the Institute of Education Sciences (#R305D190053). Co-PI Jianshen Chen.
  • 2011-2016 – Amount: $3,496,812.00, “Longitudinal Study Of Vocabulary Growth And Phonological Development,” Awarded By: National Institute of Deafness and other Communicative Disorders, David Kaplan, Co-Principal; Jan Edwards, Principal; Mary Beckman, Co-Principal; Benjamin Munson, Co-Principal.
  • 2011-2014 – Amount: $566,397.00, “Bayesian Inference For Experimental And Observational Studies In Education,” Awarded By: Institute of Educational Sciences, David Kaplan, Principal.
  • 2010-2014 – Amount: $1,600,000.00, “Validating Universal Screening And Progress Monitoring Instruments For Use With Ells In Response-To- Intervention Models.,” Awarded By: Institute of Education Sciences, Sponsor Type: Federal, David Kaplan, Co-Principal; Craig A. Albers, Principal; Thomas R. Kratochwill, Co-Principal.

Selected Publications

  • Kaplan, D. & Yavuz, S. (2019). An approach to addressing multiple imputation model uncertainty using Bayesian model averaging. Multivariate Behavioral Research.                 Download Publication
  • 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.
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  • Park, S., Steiner, P., & Kaplan, D. (2018). Identification and sensitivity analysis for average causal mediation effects with time-varying treatments and mediators: Investigating the underlying mechanisms of kindergarten retention policy. Psychometrika.
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  • Kaplan, D. & Lee, C. (2018). Optimizing prediction using Bayesian model averaging: Examples using large-scale educational assessments. Evaluation Review.
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  • Lee, Y. & Kaplan, D. (2018). Generating multivariate ordinal data via entropy principles. Psychometrika, 83, 156–181.
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  • Kaplan, D. (2016). Causal inference with large-scale assessments in education: A Bayesian perspective.Large-Scale Assessments in Education, 4,
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  • Kaplan, D., & Lee, C. (2016). Bayesian model averaging over directed acyclic graphs with implications for the predictive performance of structural equation models. Structural Equation Modeling: A Multidisciplinary Journal.
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  • Kaplan, D., & Su, D. (2016). On matrix sampling and imputation of context questionnaires with implications for the generation of plausible values in large-scale assessments. Journal of Educational and Behavioral Statistics. 41, 57-80.
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  • Park, S., & Kaplan, D. (2015). Bayesian causal mediation analysis for group randomized designs with homogenous and heterogenous treatment effects: Simulation and Case Study. Multivariate Behavioral Research. 50, 316-333.
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  • Chen, J., & Kaplan, D. (2015). Covariate Balance in Bayesian Propensity Score Approaches for Observational Studies. Journal of Research on Educational Effectiveness. 8, 280-302.
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  • Kaplan, D., & Chen, J. (2014). Bayesian model averaging for propensity score analysis. Multivariate Behavioral Research. 49, 505-517.
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  • Kaplan, D. (2014). Bayesian statistics for the social sciences. New York: Guilford Press.
  • van de Schoot, R., Kaplan, D., Dennisen, J., Asndorpf, J.B., Neyer, F.J., & van AKen, M. (2013). A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research. Child Development. 85, 842-860.
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  • Kaplan, D., & Depaoli, S. (2013). Bayesian statistical methods. In T. D. Little (Eds.), Oxford Handbook of Quantitative Methods, (pp. 407-437). Oxford: Oxford University Press.
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  • Kaplan, D., & McCarty, A.T. (2013). Data fusion with international large scale assessments: A case study using the OECD PISA and TALIS surveys. Large-scale Assessments in Education. 1(6), doi: 10.1186/2196-0739-1-6.
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  • Kaplan, D., & Chen, J. (2012). A Two-Step Bayesian Approach for Propensity Score Analysis: Simulations and Case Study. Psychometrika. 77, 581-609.
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  • Kaplan, D., & Depaoli, S. (2012). Bayesian structural equation modeling. In R. Hoyle (Eds.), Handbook of Structural Equation Modeling, (pp. 650-673). Guilford Publications Inc.
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  • Kaplan, D., & Keller, B. (2011). A note on cluster effects in latent class analysis. Structural Equation Modeling. 18, 526-536.
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Books and Edited Volumes

  • Kuger, S., Klieme, E., Jude, N. & Kaplan, D. (Eds.) (2016). Assessing Contexts of Learning: An International Perspective. Heidelberg, Springer.
  • Kaplan, D. (2014). Bayesian Statistics for the Social Sciences. New York: Guilford Press.
  • Kaplan, D. (2009). Structural Equation Modeling: Foundations and Extensions (2nd Edition). Newbury Park, CA: SAGE Publications.
  • Kaplan, D. (Ed.) (2004). The SAGE Handbook of Quantitative Methodology in the Social Sciences. Newbury Park, CA: SAGE Publications.
  • Kaplan, D. (2000). Structural Equation Modeling: Foundations and Extensions. Newbury Park, CA: Sage Publications.

Selected Invited Addresses

  • Kaplan, D. (2019). Recent Developments and Future Directions in Bayesian Model Averaging. Donald
    O. Hebb Lecture Series. Department of Psychology, McGill University, Nov. 1st., 2019, Montreal,
    Canada.
  • Kaplan, D. (2019). Quantifying Uncertainty in Models and Methods: Overview and Recent Developments
    in Bayesian Model Averaging. Invited talk, Department of Psychology, Fordham University,
    Oct. 30th, 2019, New York City, NY.
  • Kaplan, D. (2019). The Bayesian Revolution and Why You Should Care. The 2019 Anastasi Lecture.
    Fordham University, Oct. 29th, 2019, New York City, NY.
  • Kaplan, D. (2019). Quantifying Uncertainty in Models and Methods: Overview and Recent Developments
    in Bayesian Model Averaging. Invited Distinguished Lecture, Department of Psychology,
    University of California – Davis, Oct. 17th, 2019, Davis, CA.
  • Kaplan, D. (2019). An Approach to Addressing Multiple Imputation Model Uncertainty Using Bayesian
    Model Averaging. Invited paper presented at DAGStat 2019 (Deutsche Arbeitsgemeinschaft Statisk),
    Munich, Germany.
  • Kaplan, D. (2019). Quantifying Uncertainty in Models and Methods: A Bayesian Perspective. Invited
    talk, Luxembourg Institute for Socio-Economic Research. January, 16th, 2019, Belval, Luxembourg.

Presentations

  • Kaplan, D. (2019). Bayesian Probabilistic Forecasting with Implications for the United Nations Sustainable Development Education Goals. Paper presented at the annual meeting f the Society of Multivariate Experimental Psychology, October 10-12, 2019, Baltimore, MD.
  • Kaplan, D. & Yavuz, S. (2019.) An Approach to Addressing Multiple Imputation Model Uncertainty Using Bayesian Model Averaging. Paper presented at the International Meeting of the Psychometric Society. July 15 – 19, 2019, Santiago, Chile.
  • Kaplan, D. & Stancel-Piatak, A. (2019). Optimally Predictive Cross-Country Growth Models with Applications to TIMSS. Paper presented at the 8th IEA International Research Conference. June 26–28, 2017, Copenhagen, Denmark.
  • Kaplan, D. (2019). Development and Application of Cross-Country Growth Regressions Using International Large-Scale Educational Assessments. Paper presented at the 2019 annual meeting of the Population Association of America. April 11 – 13, 2019, Austin, Texas.

Awards and Honors

  • Samuel J. Messick Award for Distinguished Scientific Contributions
    Organization: American Psychological Association (Division 5)
    Date(s): August, 2018
  • Visiting Professor
    Organization: Department of Statistics and Econometrics, University of Bamberg, Germany
    Date(s): June 1 – July 31, 2018
  • Faculty Distinguished Achievement Award
    Organization: School of Education, UW-Madison
    Date(s): 2016
  • Humboldt Research Award
    Organization: Alexander von Humboldt Foundation
    Date(s): 2015 – 2016
  • Elected Member, National Academy of Education
    Date(s): 2015
  • Honorary Research Fellow, University of Oxford
    Organization: Department of Education, University of Oxford
    Date(s): 2015
  • Kellett Mid-Career Award
    Organization: Wisconsin Alumni Research Foundation
    Purpose: Scholarship/Research
    Date(s): July 1, 2012
  • Fellow, American Psychological Association (Division 5)
    Date(s): August 2010
  • Vilas Associate Award
    Organization: Wisconsin Alumni Research Foundation
    Date(s): September 2008 – June 2010
  • Distinguished Faculty Award
    Organization: School of Education, University of Delaware
    Date(s): May 2006
  • AERA Publications Committee Award for Outstanding Reviewing (2003, 2004, 2006)
    Organization: Journal of Educational and Behavioral Statistics
    Date(s): 2003
  • Jeanne Griffiths Fellow
    Organization: National Center for Education Statistics
    Date(s): 2001 – 2002
  • Elected Member, Society for Multivariate Experimental Psychology
    Date(s): 2001

Memberships

  • American Statistical Association
  • International Society for Bayesian Analysis
  • National Council on Measurement in Education
  • Population Association of America
  • Psychometric Society
  • Society for Multivariate Experimental Psychology (Elected member in 2001)

Education

  • PhD, Education, Quantitative Methods, University of California – Los Angeles
  • MA, Education, Quantitative Methods, University of California – Los Angeles
  • BA, Psychology, California State University – Northridge