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Faculty - Statistics

  • Professor


  • (Ph.D.) 2007, Statistics, University of Florida
  • (M.S.) 1997, Statistics, Kyungpook National University
  • (B.S.) 1995, Statistics, Kyungpook National University


  • 2012 – Present, Sungkyunkwan University, Assistant Professor/Associate Professor/Full Professor.
  • 2007 – 2012 Louisiana State University Health Sciences Center Assistant Professor
  • 2011 – 2012 Louisiana Chapter of American Statistical Association, vice president

Research Interest

  • Longitudinal data analysis, generalized linear models, Bayesian modeling

Research Keyword

  • categorical data analysis
  • marginalized model
  • generalized linear model

Major Research Achievements

  • Lee, K., Cho, H., Kwak, M.-S and Jang, E. (2020). Estimation of covariance matrix of multivariate longitudinal data using modified Choleksky and hypersphere decompositions. Biometrics, 76, 75-86.
  • Lee, K., Baek, C., and Daniels, M. J. (2017). ARMA Cholesky factor models for the covariance matrix of linear models. Computational Statistics & Data Analysis, 115, 267-280.
  • Lee, K., Sohn, I., and Kim, D. (2016). Analysis of long series of longitudinal ordinal data. Computational Statistics & Data Analysis. 94, 363-371.
  • Lee, K. and Yoo, J. (2014). Bayesian Cholesky factor models in random eects covariance matrix for generalized linear mixed models. Computational Statistics & Data Analysis. 80, 111-116.
  • Lee, K. and Daniels, M. (2013). Causal inference for bivariate longitudinal quality of life data in presence of death using global odds ratios. Statistics in Medicine. 32, 4275-4284.
  • Lee, K., Daniels, M., and Joo, Y. (2013). Flexible marginalized models for bivariate longitudinal ordinal data. Biostatistics. 14, 462-476.
  • Lee, K., Yoo, J. K., Lee, J., and Hagan, J. (2012). Modeling the random effects covariance matrix for the generalized linear mixed models. Computational Statistics & Data Analysis. 56, 1545-1551.
  • Lee, K., Joo, Y., Song, J. J. and Harper D. (2011). Analysis of zero-inated clustered count data: A marginalized model approach. Computational Statistics & Data Analysis. 55, 824-837.
  • Lee, K., Daniels, M., and Sargent, D. (2010). Causal eects of treatments for informative missing data due to progression/death. Journal of the American Statistical Association. 105, 912-929.
  • Lee, K., Joo, Y., Yoo, J. K., and Lee, J. (2009). Marginalized random eects models for multivariate longitudinal binary data. Statistics in Medicine, 28, 1284-1300.
  • Lee, K. and Daniels, M. (2008). Marginalized models for longitudinal ordinal data with application to quality of life studies. Statistics in Medicine. 27, 4359-4380.
  • Lee, K. and Daniels, M. (2007). A class of Markov models for longitudinal ordinal data. Biometrics. 63, 1060-1067.