Dr. MinJae Lee joined Department of Population & Data Sciences as an Associate Professor in March, 2020. She is currently an Associate Professor of Biostatistics in Peter O’Donnell Jr. School of Public Health. Dr. Lee also serves as Chair of Population Science Protocol Review and Monitoring Committee (PRMC) at Harold C. Simmons Comprehensive Cancer Center. 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's research focus centers around developing and applying innovative statistical methods to solve challenges and issues found in everyday research settings. She has gained extensive experience working at multidisciplinary research units of academic medical centers, developing successful collaborations with research investigators of various specialties. Dr. Lee has actively participated in publications and grant submissions for the various studies that require advanced statistical methodology such as cancer prevention/behavioral intervention trial design/evaluation, acute/chronic disease biomarker analysis, highly correlated maternal/child health data analysis, and multi-site/multi-level/longitudinal data modeling. As a result of her extensive collaborative scientific research activities, Dr. Lee became familiar with varying levels of statistical 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.
- 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
- Hepatocellular carcinoma surveillance may be associated with potential psychological harms of in patients with cirrhosis.
- Narasimman M, Hernaez R, Cerda V, Lee M, Sood A, Yekkaluri S, Khan A, Quirk L, Liu Y, Kramer JR, Craddock Lee S, Murphy CC, Tiro JA, Singal AG, Hepatology 2023 Jul
- Sex differences in outcomes of people with cystic fibrosis treated with elexacaftor/tezacaftor/ivacaftor.
- Wang A, Lee M, Keller A, Jian S, Lowe K, Finklea JD, Jain R, J Cyst Fibros 2023 May
- Editorial: Women in science: life-course epidemiology and social inequalities in health 2022.
- Lee M, Front Public Health 2023 11 1202171
- Participant engagement in a community health worker-delivered intervention and type 2 diabetes clinical outcomes: a quasiexperimental study in MexicanAmericans.
- Reininger BM, Lopez J, Zolezzi M, Lee M, Mitchell-Bennett LA, Xu T, Park SK, Saldana MV, Perez L, Payne LY, Collier C, McCormick JB, BMJ Open 2022 Nov 12 11 e063521
- Intensive Blood Pressure Lowering in Patients With Malignant Left Ventricular Hypertrophy.
- Ascher SB, de Lemos JA, Lee M, Wu E, Soliman EZ, Neeland IJ, Kitzman DW, Ballantyne CM, Nambi V, Killeen AA, Ix JH, Shlipak MG, Berry JD, J Am Coll Cardiol 2022 Oct 80 16 1516-1525
- Identifying Trajectories of Radiographic Spinal Disease in Ankylosing Spondylitis: A 15-year follow up study of the PSOAS Cohort.
- Hwang MC, Lee M, Gensler LS, Brown MA, Tahanan A, Rahbar MH, Hunter T, Shan M, Ishimori ML, Reveille JD, Weisman MH, Learch TJ, Rheumatology (Oxford) 2021 Aug
- Maternal obesity, pregnancy weight gain, and birth weight and risk of colorectal cancer.
- Murphy CC, Cirillo PM, Krigbaum NY, Singal AG, Lee M, Zaki T, Burstein E, Cohn BA, Gut 2021 Aug
- A latent class based imputation method under Bayesian quantile regression framework using asymmetric Laplace distribution for longitudinal medication usage data with intermittent missing values.
- Lee M, Rahbar MH, Gensler LS, Brown M, Weisman M, Reveille JD, J Biopharm Stat 2020 30 1 160-177
- A generalized weighted quantile sum approach for analyzing correlated data in the presence of interactions.
- Lee M, Rahbar MH, Samms-Vaughan M, Bressler J, Bach MA, Hessabi M, Grove ML, Shakespeare-Pellington S, Coore Desai C, Reece JA, Loveland KA, Boerwinkle E, Biom J 2019 07 61 4 934-954
- A nonparametric method for assessment of interactions in a median regression model for analyzing right censored data.
- Lee M, Rahbar MH, Talebi H Stat Methods Med Res 2018 Jan 962280217751518