University of Wisconsin–Madison

Jee-Seon Kim

Professor

jeeseonkim@wisc.edu

(608) 262-0741

1075E Educational Sciences
1025 West Johnson St.
Madison, WI 53706-1706

Personal Biography

Jee-Seon Kim is Professor in the Department of Educational Psychology and is also affiliated with the Interdisciplinary Training Program in the Education Sciences and the Center for Health Enhancement Systems Studies at the University of Wisconsin-Madison. Her research focuses on developing and applying statistical models to address practical issues in the behavioral sciences. Her research interests include multilevel modeling, imputation of missing data, longitudinal data analysis, latent variable modeling, and propensity score analysis. She has been a fellow of the Spencer Foundation, consulting editor for Psychological Methods, and book review editor for Psychometrika.

Research Interests

My research interests are concerned with the development and application of quantitative methods in the social and behavioral sciences. I am particularly interested in multilevel models and other latent variable models, methods for modeling change, learning, and human development using longitudinal data, categorical data analysis, and issues related to omitted variables. I have explored various applications of these methods for studying individual differences, patterns of change, and school effectiveness. I enjoy connecting theoretical models to real-world problems and have sought to use methodology to address practical issues in the behavioral sciences. I find this interdisciplinary aspect of my work to be rewarding and exciting, as it provides a strong sense of purpose to my ongoing research program.

Grants and Sponsorships

  • 2016-2021 – Amount: $3,691,060.00, “Test Of A Workforce Development Intervention To Ex-Pand Buprenorphine Prescribers,” Awarded By: National Institutes of Health/National Institute on Drug Abuse, Grant Institution: University of Wisconsin, .
  • 2014-2018 – Amount: $2,921,218.00, “Bio-Sphere: Fostering Deep Learning Of Complex Biology For Building Our Next Generation’s Scientists,” Awarded By: NSF, Grant Institution: University of Wisconsin, Sadhana Puntambekar, Principal; Jee-Seon Kim, Co-Principal.
  • 2014-2018 – Amount: $1,464,256.00, “Science Inquiry Using Physical And Virtual Experiments: Systematic Investigation Of Issues And Conditions For Learning,” Awarded By: NSF, Grant Institution: University of Wisconsin, Sponsor Type: Federal, Sadhana Puntambekar, Principal; Jee-Seon Kim, Co-Principal.
  • 2013-2017 – Amount: $1,599,991.00, Awarded By: Institute of Education Sciences, US Department of Education, Grant Institution: University of Wisconsin-Madison, Sponsor Type: Federal, Jee-Seon Kim; Maria Alibali, Principal.
  • 2012-2017 – Amount: $2,787,779.00, “Social Perception And Social Communication In Adults With Traumatic Brain Injury,” Awarded By: NIH, Sponsor Type: Federal, Jee-Seon Kim; Lyn Turkstra, Principal.
  • 2012-2017 – Amount: $2,986,128.00, “To Test A Payer/treatment Agency Intervention To Increase Use Of Buprenorphine,” Awarded By: NIH/NIDA, Sponsor Type: Federal, Jee-Seon Kim; Todd Molfenter, Principal.
  • 2011-2016 – Amount: $9,952,788.00, “Active Aging Research Center: Bringing Communities And Technology Together For Healthy Aging,” Awarded By: Agency for Healthcare Research and Quality, Grant Institution: University of Wisconsin, Sponsor Type: Federal, Jee-Seon Kim; David H. Gustafson, Principal.
  • 2012-2015 – Amount: $588,028.00, “Matching Strategies For Observational Studies With Multilevel Data,” Awarded By: Institute of Education Sciences, US Department of Education, Sponsor Type: Federal, Jee-Seon Kim, Co-Principal; Peter Steiner, Principal.
  • 2012-2015 – Amount: $939,935.00, “The Impact Of Early Algebra On Students’ Algebra-Readiness,” Awarded By: National Science Foundation, Jee-Seon Kim; Eric Knuth, Principal.
  • 2011-2013 – Amount: $1,097,749.00, “Discovery Research K-12: Developing Algebra-Ready Students For Middle School: Exploring The Impact Of Early Algebra,” Awarded By: National Science Foundation, Grant Institution: University of Massachusetts Dartmouth, Sponsor Type: Federal, Jee-Seon Kim; Maria Blanton, Principal.
  • 2008-2013 – Amount: $8,649,891.00, “Using Technology To Enhance Cancer Communication And Improve Clinical Outcomes,” Awarded By: National Cancer Institute, Grant Institution: University of Wisconsin, Sponsor Type: Federal, Jee-Seon Kim; David H. Gustafson, Principal.

Publications

  • Kim, J.S., Steiner, P.M., & Lim, W.C. (in press). Mixture modeling strategies for causal inference with multilevel data. Advances in Multilevel Modeling for Educational Research: Addressing Practical Issues Found in Real-World Applications.
  • Kim, J.S., & Steiner, P.M. (in press). Multilevel propensity score methods for estimating causal effects: A latent class modeling strategy. International Meeting of Psychometric Society Proceedings.
  • Keller, B., Kim, J.S., & Steiner, P.M. (in press). Neural networks for propensity score estimation: Simulation results and recommendations. International Meeting of Psychometric Society Proceedings.
  • Ellingson, L.D., Koltyn, K.F., Kim, J.S., & Cook, D.B. (2014). Does exercise induce hypoalgesia through conditioned pain modulation? Psychophysiology. 51, 267–276.
  • Bolt, D.M., Lee, Y., & Kim, J.S. (2014). Measurement and control of response styles using anchoring vignettes: A model based approach. Psychological Methods.
    Online Publication/Abstract
  • Kim, J.S., Anderson, C.J., & Keller, B.S. (2014). Multilevel analysis of assessment data. A handbook of international large-scale assessment: Background, technical issues, and methods of data analysis, (pp. 389-424).
  • Anderson, C., Kim, J.S., & Keller, B. (2014). Multilevel modeling of categorical response variables. A handbook of international large-scale assessment: Background, technical issues, and methods of data analysis, (pp. 481-519).
  • Kover, S.T., Pierpoint, E.I., Kim, J.S., Brown, T.W., & Abbeduto, L. (2013). A neurodevelopmental perspective on the acquisition of nonverbal cognitive skills in adolescents with fragile X syndrome. Developmental Neuropsychology. 38, 445–460.
  • Keller, B., Kim, J.S., & Steiner, P. (2013). Data mining alternatives to logistic regression for propensity score estimation: Neural networks and support vector machines. Multivariate Behavioral Research. 48, 164.
  • Steiner, P.M., Kim, J.S., & Thoemmes, F. (2013). Matching strategies for observational multilevel data. Joint Statistical Meeting Proceedings. Social Statistics Section, 5020-5032.
  • Kim, S.Y., Suh, Y., Kim, J.S., Albanese, M., & Langer, M. (2013). Single and Multiple ability estimation in the SEM framework: A non-informative Bayesian estimation approach. Multivariate Behavioral Research. 48, 563–591.
  • Molfenter, T., Kim, J.S., & Quanbeck, A. (2013). Testing use of payers to facilitate evidence-based practice adoption: Protocol for a clusterrandomized trial. Implementation Science. 8(50).
  • Kim, S.Y., & Kim, J.S. (2012). Investigating stage-sequential growth mixture models with multiphase data. Structural Equation Modeling. 19, 293-319.
  • Feldman, E., Kim, J.S., & Elliott, S.N. (2011). The effects of accommodations on adolescents’ self-efficacy and test performance. Journal of Special Education. 45, 77-88.
  • Kim, J.S. (2010). Within-subjects designs. In N. Salkind (Eds.), Encyclopedia of research design, (pp. 28-34). Thousand Oaks, CA: SAge.
  • Kim, J.S., & Swoboda, C.M. (2010). Handling omitted variable bias in multilevel models: Model specification tests and robust estimation. In J.J. Hox & J.K. Roberts (Eds.), Handbook of advanced multilevel analysis, (pp. 197-217).
  • McDuffie, A., Abbeduto, L., Lewis, P., Kim, J.S., Kover, A., Weber, A., & Brown, W. (2010). Autism spectrum disorder in children and adolescents with fragile X syndrome: Within-syndrome differences and age-related changes. American Journal on Intellectual and Developmental Disabilities. 115, 307-326.
  • Kim, J.S. (2009). Multilevel analysis: An overview and some contemporary issues. In R.E. Millsap & A. Maydeu-Olivares (Eds.), Handbook of quantitative methods in psychology, (pp. 337-361). Sage.
  • Frees, J.W., & Kim, J.S. (2008). Panel studies. Handbook of Probability: Theory and Applications.
  • Kim, J.S., & Bolt, D.M. (2007). Estimating item response theory models using Markov Chain Monte Carlo. Educational Measurement: Issues and Practice. pp. 38-51.
  • Kim, J.S., & Frees, E.W. (2007). Multilevel modeling with correlated effects. Psychometrika. 72, 505-533.
  • Frees, E.W., & Kim, J.S. (2006). Multilevel model prediction. Psychometrika. 71, 79-104.
  • Kim, J.S., & Frees, E.W. (2006). Omitted variables in multilevel models. Psychometrika. 71, 659-690.
  • Kim, J.S. (2006). Using the distractor categories of multiple-choice items to improve IRT linking. Journal of Educational Measurement. 43, 193-213.
  • Kim, J.S. A latent-change scaling model for longitudinal multiple choice data. Unpublished Manuscript, University of Wisconsin, Madison. 40, 53-82.
  • Bolt, D.M., & Kim, J.S. (2005). Hierarchical IRT models. Encyclopedia of behavioral sciences, (pp. 805-810).

Presentations

  • Kim, J.S., & Steiner, P.M. (2015). Causal inference with observational multilevel Data: Challenges & Strategies, International Meeting of the Psychometric Society, Beijing, China.
  • Steiner, P.M., & Kim, J.S. (2015). Estimating treatment effects via multilevel matching within homogenous groups of clusters, Society for Research on Educational Effectiveness, Washington, DC.
  • Kim, J.S., Steiner, P.M., & Lim, W.C. (2014). Multilevel propensity score methods for estimating causal effects, Advances in Multilevel Modeling for Educational Research: Addressing Practical Issues Found in Real-World Applications, College Park, MD.
  • KIm, J.S., & Steiner, P.M. (2014). Multilevel propensity score methods for estimating causal effects, The International Meeting of Psychometric Society, Madison, WI.
  • Keller, B., Kim, J.S., & Steiner, P. (2013). Alternatives to logistic regression for propensity score estimation: Neural networks, support vector machines and random forests, Society for Research on Educational Effectiveness, Washington, EC.
  • Kim, J.S., Steiner, P., Hall, C., & Thoemmes, F. (2013). Within-cluster and acrosscluster matching with observational multilevel data, Society for Research on Educational Effectiveness, Washington, DC.
  • Steiner, P., Kim, J.S., & Thoemmes, F. (2012). Matching strategies for observational multilevel data, Joint Statistical Meeting of American Statistical Association, San Diego, CA.
  • Kim, J.S., & Swoboda, C. (2012). Strategies for imputing missing values in hierarchical data: Multilevel multiple imputation, American Educational Research Association, Vancouver, Canada.
  • Kim, S.Y., & Kim, J.S. (2010). Investigating Stage-Sequential Growth Mixture Models for Multiphase Longitudinal Data, International Meeting of the Psychometric Society, Psychometric Society, Athens, GA.
  • Kim, J.S., & Swoboda, C.M. (2010). Multilevel multiple imputation using R, International Meeting of the Psychometric Society, Psychometric Society, Athens, GA.
  • Swoboda, C.M., & Kim, J.S. (2010). A simulation study of multiple imputation methods with multilevel data, Annual Meeting of American Educational Research Association, AERA, Denver, CO.
  • Kim, J.S., & Swoboda, C.M. (2010). Theory of multiple imputation methods with multilevel data, Annual Meeting of American Educational Research Association, AERA, Denver, CO.
  • Abbeduto, L., Kover, S., Porter, E., Schroeder, S., Kim, J.S., & Brown, W. (2009). Resolving misunderstandings: A longitudinal investigation of social language skills in males with fragile X syndrome, Society for the Study of Behavioral Phenotypes, Cambridge, England.
  • Kover, S.T., Kim, J.S., Abbeduto, L., & Brown, W.T. (2008). Change and stability in nonverbal cognitive abilities in girls and boys with fragile X syndrome, International Fragile X Conference, St. Louis, MO.
  • Kim, J.S., Frees, E.W., & Swoboda, C.M. (2008). Multilevel Model Specification Tests Using the Generalized Methods of Moment (GMM) Estimation Techniques, Annual International Meeting of the Psychometric Society, Durham, NH.
  • Kim, J. (2008). Handling Omitted Variable Bias in the Analysis of Educational Data: Diagnostics and Remedies Using Multilevel Modeling Techniques, School of Education, University of Wisconsin-Madison, Madison, WI.
  • Kim, J., & Swoboda, C.M. (2007). A study of omitted variable bias in multilevel models for the NELS:88 Data, Annual Meeting, AMerican Educational Research Association, Chicago, IL.

Departmental Service

  • Faculty Affairs Committee
    Dates of Membership: 2009 – 2012 Committee Chair. Period of Service: 2010 – 2011
  • Quantitative Methods Faculty Search Committee
    Dates of Membership: Sep. 2009 – Feb. 2010 Committee Chair. Period of Service: Sep. 2009 – Feb. 2010

School Service

  • Institutional Research Board (IRB)
    Dates of Membership: 2011 – Present

Public Service

  • Psychological Methods
    Dates of Membership: 2016 – Pres.
  • Associate Editor.
  • Psychometrika
    Dates of Membership: 2016 – Pres.
  • Associate Editor.
  • Jason Millman Award for Promising Measurement Scholar
    Dates of Membership: 2009 – 2012
  • Committee Chair. Period of Service: 2011 – 2012
  • Institute of Education Sciences
  • Principal Panel Member. Period of Service: 2011 – 2014

Education

  • BA, Statistics
  • MS, Statistics
  • PhD, Quantitative Psychology
    University of Illinois at Urbana-Champaign