Lee-Jen Wei

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Developing Quantitative Methods for Designing, Monitoring, and Analyzing Clinical Studies


Our research focuses on developing statistical methods for the design and analysis of clinical trials. In the late 1970s, Dr. Wei introduced the "urn design" for two-arm sequential clinical studies, a design that has since been used in several large-scale multicenter trials. Later he proposed a response adaptive design, currently utilized in several trials sponsored by private industry, to ameliorate problems arising from the conventional rule of 50-50 randomization treatment allocation in clinical studies. In the 1980s, he presented a monitoring scheme for the interim analysis for clinical trial data.


We have also developed numerous methods for analyzing data with multiple outcomes or repeated measurements from study subjects, in particular, "multivariate Cox procedures" for handling multiple event times, as well as alternatives to the Cox proportional hazards model for analyzing survival observations.


A critical issue in statistical inference is ascertaining whether the model used for the data is appropriate. Currently, we are developing graphical and numerical methods for checking the adequacy of the Cox proportional hazards model, other semi-parametric survival models, parametric models, and random effects models for repeated measurements. The new procedures are much less subjective than conventional methods based on ordinary residuals plots.


Since the cost of computing has dropped, some intractable statistical problems can now be handled numerically. Presently, we are working on various resampling methods for quantile regression, rank regression, and regression models for censored data.



Dr. Wei received his PhD in statistics from the University of Wisconsin-Madison in 1975. Since then, he has held academic appointments at the University of South Carolina, George Washington University, University of Michigan, University of Wisconsin, and Harvard University. He has also worked at the National Cancer Institute, and served as associate editor for the Journal of the American Statistical Association, Biometrics, and Communications in Statistics. Currently, he is director of the Bioinformatics Core of the Harvard School of Public Health.


Recent Publications

Tian L, Cai T, Zhao L, Wei LJ. On the covariate-adjusted estimation for an overall treatment difference with data from a randomized comparative clinical trial. Biostatistics. 2012 Apr; 13(2):256-73.


Claggett B, Wei LJ. Analytical issues regarding rosiglitazone meta-analysis. Arch Intern Med. 2011 Jan 24; 171(2):179-80; author reply 180.


Tian L, Wang R, Cai T, Wei LJ. The highest confidence density region and its usage for joint inferences about constrained parameters. Biometrics. 2011 Jun; 67(2):604-10.


Li Y, Tian L, Wei LJ. Estimating subject-specific dependent competing risk profile with censored event time observations. Biometrics. 2011 Jun; 67(2):427-35.


Price AL, Kryukov GV, de Bakker PI, Purcell SM, Staples J, Wei LJ, Sunyaev SR. Pooled association tests for rare variants in exon-resequencing studies. Am J Hum Genet. 2010 Jun 11; 86(6):832-8.


Elkayam U, Janmohamed M, Hatamizadeh P, Heywood JT, Wei LJ, Mills RM. Impact of acute serum creatinine elevation in patients treated with nesiritide. Clin Cardiol. 2009 Apr; 32(4):215-9.


Zhou H, Wei LJ, Xu X, Xu X. Combining association tests across multiple genetic markers in case-control studies. Hum Hered. 2008; 65(3):166-74.


Dienstag JL, Wei LJ, Xu D, Kreter B. Cross-study analysis of the relative efficacies of oral antiviral therapies for chronic hepatitis B infection in nucleoside-naive patients. Clin Drug Investig. 2007; 27(1):35-49.


Feng Y, Hong X, Li Z, Zhang W, Jin D, Liu X, Zhang Y, Hu FB, Wei LJ, Zang T, Xu X, Xu X. Prevalence of metabolic syndrome and its relation to body composition in a Chinese rural population. Obesity (Silver Spring). 2006 Nov; 14(11):2089-98.


Wang L, Feng Y, Zhang Y, Zhou H, Jiang S, Niu T, Wei LJ, Xu X, Xu X, Wang X. Prolylcarboxypeptidase gene, chronic hypertension, and risk of preeclampsia. Am J Obstet Gynecol. 2006 Jul; 195(1):162-71.

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