Jeremy M G Taylor, Ph.D.
- Professor, Department of Biostatistics
- Pharmacia Research Professor, Department of Biostatistics
- Professor, Department of Radiation Oncology
- Professor, Department of Computational Medicine and Bioinformatics
- Associate Director for Biostatistics, Comprehensive Cancer Center
- Professor, Department of Biostatistics
- M4509 SPH II
- 1415 Washington Heights
- Ann Arbor, Michigan 48109-2029
- B.A., Honours Mathematics, Cambridge University, 1978
- Dip. Stat., Statistics, Cambridge University, 1979
- Ph.D., Statistics, University of California, Berkeley, 1983
Research Interests & Projects
My interests are the theory and application of statistics to biomedical problems. I believe that data-driven, robust, flexible statistical methods should be used, incorporating scientific knowledge from the substantive area of investigation. A good statistician has to be heavily involved in the underlying science of the data he/she is investigating.
My research has focused on the application of statistics to cancer and AIDS, especially to radiation oncology. The specific areas are modelling, survival analysis and longitudinal data. This has led to developing methods involving the use of mixture models, stochastic processes and multiple imputation.
My theoretical statistical interests are in Box-Cox power transformations, robust methods, nonparametrics and smoothing techniques.
My previous research in radiation oncology has focussed on the effect of fraction size, total dose, time and volume on the biological response to radiation. I have studied the response of both tumours and normal tissues to radiation.
My work related to cancer has focused on modelling and evaluating biomarkers, particularly PSA in prostate cancer. More recent applied work has been concerned with methods for combining multiple biomarkers, methods for analysing data from gene expression arrays, evaluation of surrogate and auxiliary variables and design of phase I trials in oncology.
- Li Y, Taylor JMG, Elliot MR, Sargent D: "Causal Assessment of Surrogacy in a Meta Analysis of Colorectal Cancer Trials" Biostatistics 12(3): 478-492, 2011.
- Foster, JC, Taylor, JMG, and Ruberg, SJ: “Subgroup Identification from Randomized Clinical Trial Data.” Stats Med, 30(24): 2867-80, 2011.
- Park Y, Taylor JMG and Kalbfleisch JD: “Constrained Nonparametric Maximum Likelihood Estimation of Stochastically Ordered Survivor Functions.” Canad J Statist, 40: 22-39, 2012.
- Park YS, Taylor JMG, Kalbfleisch J: "Pointwise Nonparametric Maximum Likelihood Estimator of Stochastically Ordered Survivor Functions". Biometrika, 99(2): 327-343, 2012.
- Boonstra P, Taylor JMG, Mukherjee B: "Incorporating Auxiliary Information for Improved Prediction in High Dimensional Datasets: An Ensemble of Shrinkage Approaches." Biostatistics, 14(2): 259-72, 2013.
- Taylor JMG, Park Y, Ankerst DP, Proust-Lima C, Williams S, Kestin L, Bae K, Pickles T, Sandler H: “Real-Time Individual Predictions of Prostate Cancer Recurrence Using Joint Models.” Biometrics, 69(1): 206–213, 2013.
- McShane LM, Cavenagh MM, Lively TG, Eberhard DA, Bigbee WL, Williams PM, Mesirov JP, Polley MYC, Kim KY, Tricoli JV, Taylor JMG, Shuman DJ, Simon RM, Doroshow JH, Conley BA: “Criteria for the Use of Omics-Based Predictors In Clinical Trials.” Nature, 502(7471):317-20, 2013.
- Park Y, Kalbfleisch JD, Taylor JMG: “Confidence Intervals under Order Restriction.” Statistica Sinica, 24:429-445, 2014.
- Boonstra PS, Mukherjee B, Taylor JMG: “Bayesian shrinkage methods for partially observed data with many predictors.” Annals of Applied Statistics, 7(4):2272-92, 2013.
- Conlon ASC, Taylor JMG, Sargent DJ: “Multi-State Models for Colon Cancer Recurrence and Death with a Cured Fraction.” Stat Med, 33(10):1750-66, 2014.
- Conlon AS, Taylor JMG, Elliott MR: “Surrogacy Assessment Using Principal Stratification When Surrogate and Outcome Measures are Multivariate Normal.” Biostatistics, 15(2): 266-83, 2014.
- Boonstra PS, Shen J, Taylor JMG, Braun TM, Griffith KA, Daignault SD, Kalemkerian GP, Lawrence TS. Schipper MJ: “A Statistical Evaluation of Dose Expansion Cohorts in Phase I Clinical Trials”. JNCI, 107(3):, 2015.
- Foster J, Taylor JMG, Kaciroti N, Nan B: “Simple Subgroup Approximations to Optimal Treatment Regimes from Randomized Clinical Trial Data”. Biostatistics, 16(2):368-82, 2015.
- Conlon ASC, Taylor JMG, Sargent DJ: “Improving Efficiency in Clinical Trials Using Auxiliary Information; Application of a Multi-State Cure Model.” Biometrics, 71(2):460-8, 2015.
- Rizopoulos D, Taylor JMG, van Rosmalen J, Steyerberg EW, Takkenberg JJM:
“Personalized Screening Intervals for Biomarkers Using Joint Models for longitudinal and Survival Data.”
- Beesley L, Bartlett J, Wolf G, Taylor JMG: “Multiple Imputation of Missing Covariates for the Cox Proportional Hazards Cure Model.”Stat Med, 35(26): 4701-4717, 2016.
- Prince V, Bellile EL, Sun Y, Wolf GT, Hoban CW, Shuman AG, Taylor JMG:
“Individualized Risk Prediction of Outcomes for Oral Cavity Cancer Patients
”Oral Oncology, (63):66-73, 2016.
- Rice JD, Taylor JMG: “Locally Weighted Score Estimation for Quantile
Classification in Binary Regression Models.” Stat Biosci, 8(2):333-350, 2016.
- Peng Y, Taylor JM: “Residual-Based Model Diagnosis Methods for Mixture Cure Models” Biometrics, 73(2): 495-505, 2017.
- Shen J, Wang L, Daignault S, Spratt DE, Morgan TM, Taylor JMG: “Estimating the
Optimal Personalized Treatment Strategy Based on Selected Clinical Variables to
Prolong Survival via Random Survival Forest with Weighted Boostrap.” J Biopharm Stat, 1-20, 2017.
- Shen J, Wang L, Taylor JMG: “Estimation of the Optimal Regime in Treatment of
Prostate Cancer Recurrence from Observational Data Using Flexible Weighting
Models.” Biometrics, 73(2):635-645, 2017.
- Royal Statistical Society
- American Statistical Association
- International Biometrics Society
- Institute of Mathematical Statistics
- International Statistical Institute
- Radiation Research Society