Recognized Publication / Award Citation
A. P. Dawid.
“Properties of diagnostic data distribution''. Biometrics, 32, 1976, 647-658.
Bruce W. Turnbull and Toby J. Mitchell
“Exploratory analysis of disease prevalence data from survival/sacrifice experiments”. Biometrics, 1978, 34, 555-570.
Ethel S. Gilbert
“The assessment of risks from occupational exposure to ionizing radiation''. Energy and Health, Proceedings of a Conference, 1979, 209-225.
Barry H. Margolin, Norman Kaplan, and Errol Zeiger
“Statistical analysis of the Ames /microsome test,'' Proceedings of the National Academy of Science, 78, 1981, 3779-3783.
Byron J. T. Morgan
“Modeling polyspermy''. Biometrics, 38, 1982, 885-898.
C. Brownie and D. S. Robson
“Estimation of time--specific survival rates from tag--resighting samples: a generalization of the Jolly--Seber model''. Biometrics, 39, 1983, 437-203
R. A. Maller, E. S. DeBoer, L. M. Joll, D. A. Anderson, and J. P. Hinde
“Determination of the maximum foregut volume of western rock lobsters (Panulirus ) from field data''. Biometrics, 39, 1983, 543-551.
Stuart H. Hurlbert
“Pseudoreplication and the design of ecological field experiments''. Ecological Monographs, 54 (2), 1984, 187-211
John A. Anderson
“Regression and ordered categorical variables''. Journal of the Royal Statistical Society, 46, 1984, 1-30.
Mitchell H. Gail and Richard Simon
“Testing for qualitative interactions between treatment effects and patients subsets''. Biometrics, 41, 1985, 361-372.
Kung-Yee Liang and Scott L. Zeger
“Longitudinal data analysis using generalized linear models''. Biometrika, 73, 1986, 13-22; and “Longitudinal data analysis for discrete and continuous outcomes''. Biometrics, 42, 1986, 121-130.
George E. Bonney
“Regressive logistic models for familial disease and other binary traits''. Biometrics, 42, 1986, 611-625; and
“Logistic regression for dependent binary observations''. Biometrics, 43, 1987, 951-973.
Karim F. Hirji, Cyrus R. Mehta, and Nitin R. Patel
“Exact inference for matched studies''. Biometrics, 44, 1988, 803-814.
Barry I. Graubard, Thomas R. Fears, and Mitchell H. Gail
“Effects of cluster sampling on epidemiologic analysis in population-based case-control studies''. Biometrics, 1989, 20, 1053-1071.
Kenneth H. Pollack, James D. Nichols, Cavel Brownie, and J. E. Hines
“Statistical inference for capture-recapture experiments''. Wildlife Monographs, 107, 1990, The Wildlife Society.
Kenneth L. Lange and Michael L. Boehnke
“Bayesian methods and optimal experimental design for gene mapping by radiation hybrid''. Annals of Human Genetics, 56, 1993, 119-144.
Norman E. Breslow and David Clayton
“Approximate inference in generalized linear models". Journal of the American Statistical Association, 88, 1994, 9-25.
Michael A. Newton
“Bootstrapping phylogenies: Large deviations and dispersion effects''. Biometrika, 83 (2), 1996, 315-328
Kathryn Roeder, Raymond J. Carroll and B. G. Lindsay
“A Semiparametric Mixture Approach to Case-Control Studies with Errors in Covariables''. Journal of the American Statistical Association, 91, 1996, 722-732.
Daniel Scharfstein, Anastasios "Butch" Tsiatis and Jamie Robins.
"Semiparametric Efficiency and Its Implications on the Design and Analysis of Group-Sequential Studies”. Journal of the American Statistical Association, 92, 1997, 1342-1350.
Patrick J. Heagerty
“Marginally specified logistic-normal models for longitudinal binary data”. Biometrics, 55, 1999, 688-698.
Paul R. Rosenbaum
"Effects Attributable to Treatment: Inference in Experiments and Observational Studies with a Discrete Pivot". Biometrika, 88, 2001, 219-231; and "Attributing Effects to Treatment in Matched Observational Studies". Journal of the American Statistical Association, 97, 2002, 183-192.
Nicholas P. Jewell and Mark J. van der Laan
of California, Berkeley School of Public Health
“Case-control Current Status Data”. Biometrika, 91, 2004, 529-541.
For the noteworthy publication "Case-control Current Status Data," Biometrika (2004); 91(3):529-541, which focused on identifiability and nonparametric maximum likelihood estimation of survival distributions based on case-control samples of current status data. This paper represents one contribution among many from Nicholas Jewell and Mark van der Laan, and the Committee of Presidents of Statistical Societies acknowledges the overall impact of their research in the development of statistical theory in biometry.
“The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials”, Statistics in Medicine, 26, 2007, 20-36.
For a substantial body of scholarly work that advances the use of statistics in the biological sciences in areas including, but not limited to, the EM algorithm, missing data, imputation, and causality; for a legacy of students who continue to enrich our profession; for unflagging efforts to build our profession as an administrator, editor, and author; and for keeping us focused on the governing, foundational principles that guide the development of our discipline.
North Carolina State University
“Improving efficiency of inferences in randomized clinical trials using auxiliary covariates.” Biometrics, 64,2008, 707-715 (Zhang, M., Tsiatis, A.A., and Davidian, M.).
For fundamental contributions to the theory and methodology of longitudinal data, especially nonlinear mixed effects models; for significant contributions to the analysis of clinical trials and observational studies, and for leadership as president of ENAR, as editor, and as a member of the International Biometric Society council.
Division of Cancer Epidemiology & Genetics, National Cancer Institute, USA
“Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies.” Chen YH, Chatterjee N, Carroll RJ. J Am Stat Assoc. 2009; 104: 220-233.
For groundbreaking work in statistical genetics, especially in developing powerful methods for gene-gene and gene-environment interactions in case-control, genome-wide association studies; for fundamental work in statistical methods used in epidemiological research, and for mentorship and leadership at the National Cancer Institute.
Jack D. Kalbfleisch
University of Michigan
“Pointwise nonparametric maximum likelihood estimator of stochastically ordered survivor functions” Park Y, Taylor JMG, and Kalbfleisch JD, Biometrika, 99, 327-343, 2012.
For foundational contributions to the field of biometry, especially for innovative analysis methods for failure time data, event history analysis, mixture models and likelihood theory; for influential collaborative research, especially in the area of solid organ transplantation; and for exceptional mentoring of junior researchers, exemplary senior leadership of statistical groups, and steadfast service to the profession.
University of North Carolina
“Efficient estimation of semiparametric transformation models for two-phase cohort studies”, Donglin Zeng and D.Y. Lin. Journal of the American Statistical Association, 2014: 109, 371-383.
For foundational contribution to the field of biometrics especially for semiparametric regression models with censored data. For influential work in genome-wide association studies and next-generation sequencing studies. For steadfast service to the profession.
University of Melbourne
“Nonparametric methods for group testing data, taking dilution into account”, A. Delaigle and P. Hall. Biometrika, 2015: 102, 871-887.
For fundamental and groundbreaking contributions to the statistical theory of group testing of pooled laboratory samples, and for contributions to measurement error methods and density estimation.
University of California Los Angeles
“Hierarchical nearest-neighbor Gaussian process models for large geostatistical datasets”, Datta, A., Finley, A.O. and Gelfand, A.E. Journal of American Statistical Association.
For foundational contribution to the field of biometrics, especially for groundbreaking and fundamental work on Bayesian hierarchical modeling and the analysis of large spatial datas ets; for significant contributions to the mapping of disease incidence in space and time, and the analysis of environmental exposures.
“Robust Bayesian inference via coarsening”, Miller, J.W. and Dunson, D.B. Journal of American Statistical Association, 2019: 114, 1113-1125.
For seminal and consequential advancements in the theoretical and methodological underpinnings of Bayesian modeling and inference; for significant contributions in high-dimensional statistical inference, nonparametric Bayesian modeling, and their wide-ranging applications in biomedical and natural science.