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David Oakes, PhD

David Oakes, PhDProfessor of Biostatistics and Statistics
Ph.D. (1972) London University

Contact Information

University of Rochester
Dept of Biostatistics and Computational Biology
265 Crittenden Boulevard, CU 420630 
Rochester, New York 14642-0630
Office: Saunders Research Building 4104
Phone: (585) 275-2405
Fax: (585) 273-1031

Research Interests

My major research interests are in the area of survival analysis, especially models for the effect of explanatory variables on survival and for multivariate survival data.  Much of my work has focused on  models for bivariate survival models generated by unobserved random effects, often called frailties. There are close connections with so-called “Archimedean copula” models for bivariate data. A current interest is the "win-ratio," a method of summarizing multiple outcome data in clinical trials which gives priority to the more important outcome. 

I am deeply involved in clinical trials of treatments for Parkinson’s disease and Huntington’s disease. I have also worked in cardiology, infectious diseases and pediatrics. I have a longstanding interest in occupational and environmental medicine.

I have advised or co-advised a total of eleven graduate students of whom four have become full professors (Ben Armstrong at London University, Amita Manatunga at Emory, Jong Hyeon-Jeong at Pittsburgh), and Changyong Feng at Rochester.

I am a Fellow of the American Statistical Association and of the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. I have served on the NIH Study Sections "Biostatistical Methods and Research Design" and “Epidemiology of Cancer”. From 1979-2008 I was an associate editor of the leading journal Biometrika, and currently serve as one of three Editors of the journal “Lifetime Data Analysis”. I have authored or co-authored four books and over 200 publications, including methodologic papers in the statistical and biostatistical literature and collaborative works in the medical literature, in recent years mostly in Neurology journals. A selection of the methodologic works is given below. For a c.v., that includes publications in the medical literature, click here

Selected References

  • Oakes, D. (2018). Survival models and health sequences: discussion. Lifetime Data Analysis 24, 592-594.
  • Oakes, D. (2016). On the win-ratio statistic in clinical trials with multiple types of event. Biometrika 102, 742-745.
  • Oakes, D. (2013). An introduction to survival models: in honor of Ross Prentice. Lifetime Data Analysis 19, 442-463.
  • Oakes, D. and Feng, C.Y. (2010). Combining stratified and unstratified log-rank tests in paired survival data. Statistics in Medicine 29, 1735-1745.
  • Wang, A. and Oakes, D. (2008). Some properties of the Kendall distribution in bivariate Archimedean copula models under censoring. Statistics and Probability Letters 78, 2578-2583.
  • Oakes, D. (2001). Biometrika Centenary: Survival Analysis. Biometrika 88, 99-142. Reprinted in Titterington, D.M. and Cox, D.R. (Eds.) Biometrika: One Hundred Years, Oxford; Oxford U.P., pp 97-140. (2001).
  • Manatunga, A.K. and Oakes, D. (1999). Parametric analysis of matched pairs survival data. Lifetime Data Analysis 5, 371-387.
  • Oakes, D. and Cui, L. (1994). A note on semiparametric inference for modulated renewal processes. Biometrika 81, 83-90.
  • Oakes, D. and Dasu, T. (1990). A note on residual life. Biometrika 77, 409-410.
  • Oakes, D. (1989). Bivariate survival models induced by frailties. Journal of the American Statistical Association 84, 487-493.
  • Cox, D.R. and Oakes, D. (1984). Analysis of Survival Data.  Chapman and Hall, London.
  • Oakes, D. (1982). A model for association in bivariate survival data. Journal of the Royal Statistical Society (Series B) 44, 414-422.
  • Oakes, D. (1981). Survival times: aspects of partial likelihood (with discussion). International Statistical Review 49, 235-264. 
  • Hawkes, A.G. and Oakes, D. (1974). A cluster process representation of self-exciting process. Journal of Applied Probability 11, 493-503.

Last updated March 24, 2022