Dr. MinJae Lee joined Department of Population & Data Sciences and Simmons Comprehensive Cancer Center as an Associate Professor in March, 2020. Prior to joining UTSW, she served as an Associate/Assistant Professor of Biostatistics in Division of Clinical & Translational Sciences at University of Texas McGovern Medical School, UTHealth (2012-2020), and a Research Instructor of Biostatistics at School of Medicine, Magee-Womens Research Institute, University of Pittsburgh (2010-2012). Dr. Lee received her Ph.D. degree in Biostatistics at Graduate School of Public Health, University of Pittsburgh in 2010. 

Dr. Lee has developed successful collaborations with research investigators of various specialties and actively participated in publications and grant submissions for the various studies that involve the application of advanced statistical analysis methods. As a result of her extensive collaborative/scientific research activities including cancer prevention/behavioral intervention trials, acute/chronic disease biomarkers analysis, maternal/child health studies, and multi-site longitudinal studies, Dr. Lee became familiar with varying levels of statistical/epidemiological challenges in analyzing complex data; she identified the areas requiring methodologic development and provided solutions to address clinically relevant questions by developing innovative statistical methods and illustrating their proper applications to real data. Dr. Lee developed multiple statistical approaches based on quantile regression, non-/semi-parametric statistical methods or Bayesian methodology to deal with various types of measurement errors in self-reported data, truncated/censored values due to limit of detections in biomarkers or environmental measurements, missing values in longitudinal/multi-level data under various mechanisms. She has also contributed to the university through teaching and serving on committees across campuses. She is a member of American Statistical Associations and an active reviewer/associate editor of several statistical and clinical journals.

Research Interest

  • Development of statistical methods for analyzing censored/truncated biomarkers or environmental measurements subject to detection limits
  • Imputation/estimation methods development for handling missing and/or censored values in longitudinal data
  • Measurement errors in self-reported data
  • Methodology for data management/quality assurance
  • Multi-level/longitudinal data analysis methods
  • Semi-/non-parametric statistical methods
  • Statistical analysis and design for cancer prevention/behavioral intervention trials
  • Statistical challenges of epidemiological research in maternal/child health
  • Translational research


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