- Honorary Member
- SSC Gold Medal
- Distinguished Service Award
- Pierre-Robillard Award
- CRM-SSC Prize in Statistics
- The Canadian Journal of Statistics Award
- SSC Impact Award
Honorary Member
SSC Honorary Membership: John D. Kalbfleisch
John D. (Jack) Kalbfleisch, Professor Emeritus of Biostatistics at the University of Michigan, has been named an Honorary Member of the Statistical Society of Canada. This award is intended to honor an individual who has made exceptional contributions to the development of the statistical sciences in Canada and whose work has had a major impact in this country.
Jack was born on July 16, 1943 in Grand Valley, Ontario. His family moved to Orangeville two years later and he grew up there with his older brother, Jim (also a statistician and former President of the SSC), and his younger brother and sister, Peter and Carol. Jack’s parents were both teachers; his father, who was a high school math teacher, coached Jim and Jack through their studies and did much to encourage interest and skills in mathematics. There were two moves during Jack’s high school years, to Grand Valley after 10th grade and to Goderich after 12th grade. Jack was active in all three schools in student council and drama.
Jack studied mathematics and statistics at the University of Waterloo (BSc 1966, MMath 1967, PhD 1969). After being a Research Associate at University College, London, in 1969–70, he was hired as an Assistant Professor at SUNY Buffalo. He returned to Waterloo as an Associate Professor in 1973 and was promoted to Full Professorship in 1979. He was Chair of his department from 1984 to 1990, and Dean of the Faculty of Mathematics from 1990 to 1998. From 2002 to 2006, he was Chair of the Department of Biostatistics at the University of Michigan. He was then Director of the Kidney Epidemiology and Cost Center until his retirement in 2012. Jack’s sabbatical leaves were spent at the University of California, San Francisco, the University of Washington, the University of Auckland and the National University of Singapore (twice).
In addition to his long-standing record of service as Chair and Dean, Jack has had a very impressive career as a researcher, author, and mentor. His book on The Statistical Analysis of Failure Time Data, written in collaboration with Ross Prentice, is a classic that has gone through two editions. Jack is also the author of nearly 120 research papers, published for the most part in JASA, Biometrika, JRSS B, and other top-tier journals. He has strongly influenced the development of models and methods for analyzing failure time and event history data, with applications to many areas including epidemiology, medicine, demography and engineering. He has been particularly interested in situations where the data are incomplete or subject to sampling bias. He has also studied various aspects of modeling and analyzing mixtures, including work on algorithms for fitting nonparametric mixtures and on methods for testing the order of a finite mixture, a problem arising in various applications in genetics.
In recent years Jack has been working on statistical aspects of problems associated with end-stage renal disease and solid organ transplantation. The Kidney Epidemiology and Cost Center has many large-scale projects associated with such issues, including several large contracts funded by the Centers for Medicare and Medicaid Services. This is an area where statistical methods play a key role in defining public policy.
Throughout his career Jack supervised more than 20 PhD students. Many of them have gone on to make significant contributions to the field. Jack’s record of service to the profession is equally exceptional, not only at Waterloo, but also at NSERC (e.g., as Group Chairman, 1996–98), with the institutes (Fields, PIMS, and more recently CANSSI), and within the SSC (e.g., as President in 1999–2000). In addition, he has served on the Editorial Board of several journals, including The Annals of Statistics, Biometrics, and The Canadian Journal of Statistics.
Jack’s outstanding contributions to the development of statistics earned him numerous honors and awards over the years. In particular, he was elected a Fellow of the Royal Society of Canada in 1994 and was awarded the SSC Gold Medal the same year. On the international scene, he received the Fisher Lecture Award in 1999 and the Snedecor Award for Biostatistical Research in 2013. Needless to say, he is also a long-standing Elected Member of the International Statistical Institute (1981), a Fellow of the American Statistical Association (1987), and a Fellow of the Institute of Mathematical Statistics (1988).
Jack married Sharon Allen in Hamilton, Ontario in 1966. Sharon taught at Conestoga College in Kitchener and was Dean there for a number of years. Jack and Sharon’s three children grew up in Waterloo: Michael graduated from the University of Western Ontario in dentistry and practises in Waterloo; Heidi has a Masters degree in Statistics from Simon Fraser University and works in the health care industry in Richmond, Virginia; her twin sister, Kirby, got her MBA from the University of Calgary and is a market research consultant, also home-based in Richmond. Jack and his wife live in Ann Arbor, Michigan, and recently moved to a smaller house out of town. Jack continues to contribute to a number of research projects, is an avid gardener, enjoys the many musical events in Ann Arbor and plans to get back to his earlier work on stained glass. He and Sharon also enjoy summer adventures with their five grandchildren.
The certificate that was given to Jack reads as follows:
“To John D. Kalbfleisch, for his exceptional contributions to statistics, notably in survival and event analysis; for his important and influential work in health research; for his excellence in training and mentoring; for his remarkable and sustained academic leadership; and for his dedication to the profession in Canada and abroad.”
SSC Gold Medal
SSC Gold Medal: Richard Lockhart
Richard Lockhart is Professor in the Department of Statistics and Actuarial Science at Simon Fraser University. Richard was born in Montréal in 1954 and grew up in Winnipeg, Manitoba and Tsawwassen, British Columbia. He received a BSc in Math from UBC in 1975, an MA from the University of California at Berkeley in 1976 and then a PhD in Statistics from the same university in 1979. His thesis “The Programming Operation on s-fields” was written under the supervision of David Blackwell. After a six-month post-doctoral fellowship at the Centre de recherches mathématiques at l’Université de Montréal he joined Simon Fraser University in September 1979. He has been at SFU since then except for sabbaticals at Waterloo and Oxford and a single year at the University of Toronto.
Richard is a statistical leader in Canada, through his research, his many contributions to the Statistical Society of Canada, his teaching and mentoring of students at Simon Fraser University, but most of all through his enthusiasm for good ideas and the pleasure of tackling new problems. He has had a long-standing interest in goodness-of-fit testing and, with Michael Stephens, has made a number of important contributions, from their Biometrika paper in 1985 through to his Bernoulli paper in 2012. This last paper was an elegantly written, thoughtful and very original contribution to a topic that many people have dismissed as ‘finished’. Richard showed that conditional and unconditional tests of goodness-of-fit may be expected to be nearly identical under certain conditions. The importance of this contribution will take some years to become clear; the set of remarks in the concluding discussion section outline a wealth of ideas and a number of ways the work could be investigated further.
Although known for his work in goodness-of-fit, Richard is one of our discipline’s few polymaths – he has made interesting and original contributions to a surprising variety of topics. With his Berkeley roommate, Peter Guttorp, he worked on Bayesian models for directional data, uniform limit theory for high dimensional quadratic forms and inference in Galton-Watson-Bienaymé processes. With his former student, Grace Chiu, he has written several papers on so-called ‘bent-cable’ regression. He has had an interesting collaboration with Peter Borwein investigating random polynomials; their papers appeared in the Annals of Mathematics and the Proceedings of the American Mathematical Society. He collaborated with Joan Hu in work on panel data, and with his former student, Gemai Chen, on the Box-Cox model. His collaborators would confirm that his contributions and his insight were essential to the success of the project. In the past few years he became involved in a very exciting collaboration with Rob and Ryan Tibshirani and Jonathan Taylor on asymptotic theory for lasso estimators. This is a very important topic that is only just being addressed by a handful of people working in high-dimensional data. That Richard was able to make important contributions without having an extensive background in the field is very impressive, although knowing his strengths, not surprising.
Richard’s great strength is a deep knowledge of analysis, probability, and theoretical statistics that has enabled him to solve problems in asymptotic distribution theory and rigorous justification of procedures. He has always been ready to tackle any problem brought to him and this is shown by a wide range of publications and collaborators, with major contributions to goodness-of-fit, signal processing, stochastic processes, use of the Box-Cox transformation, smoothing, and the lasso, among others.
Richard’s contributions to professional service are equally noteworthy and wide ranging, and many of these relate to research. He served as Editor of the Canadian Journal of Statistics (2001-03), and as the Statistical Society of Canada’s Executive Editor for Statistical Surveys (since 2007); he was also an Associate Editor of Technometrics from 2002-07. He has served as President of the Statistical Society of Canada (1996-97), and on numerous scientific advisory committees: for example, as a member of Statistics Canada’s Advisory Committee on Statistical Methods (1998-2012), and as a member of the ASA Advisory Committee to the Energy Information Agency (1991-96). He was a member of the Natural Sciences and Engineering Research Council of Canada’s grant selection committee for statistical science (1991-94), chairing a joint Mathematics and Statistics equipment grant selection committee in his final year. He has been the Program Chair for the Statistical Society of Canada’s Annual Meeting (2006), and has served on several other organizing committees. From 2008 to 2014, he served as Chair of the Department of Statistics and Actuarial Science at Simon Fraser University.
Richard’s contributions have been recognized before. He was elected Fellow of the American Statistical Association in 2013 and a Fellow of the Institute of Mathematical Statistics in 2014. He received the Distinguished Service Award of the SSC in 2002.
One letter writer said “Richard is the most unselfish researcher I have ever known – he enjoys every opportunity to offer his help, regardless whether the question came from his students, from his colleagues, from a paper under review, from consulting, or from an email originated far away, and he often takes no credit.”
The citation for the award reads:
“To Richard Lockhart, for outstanding contributions to statistical inference and methodology; for development of asymptotic distribution theory and rigorous justification of procedures in applied statistics through his deep knowledge of analysis, probability, and theoretical statistics; for the breadth of his contributions notably on goodness-of-fit, signal processing, stochastic processes, use of the Box-Cox transformation, smoothing, and the lasso, among others.”
Distinguished Service Award
Distinguished Service Award: Shirley Mills
Professor Shirley Mills is the recipient of the 2015 Distinguished Service Award from the Statistical Society of Canada (SSC). This award honors an individual who has played an important and substantial role in fostering the growth and success of the Canadian Statistical Sciences community through leadership in the SSC.
Shirley graduated from the University of Manitoba in 1969 with a Double Honours degree in Mathematics and Statistics with additional studies in Actuarial Science and Computer Science. This was followed by both a Masters degree in Statistics in 1970 and a Certificate in Education in 1971, also from the University of Manitoba. After a brief sojourn at Great West Life as an actuary, she taught at the University of Winnipeg in 1971-80 and at the University of Alberta in 1978-79 and 1981-83. She received her PhD in Statistics and Applied Probability from the University of Alberta in 1983 and moved to join Carleton University in September 1983. In 1987 she founded the Statistical Consulting Centre at Carleton, serving as its first Director for seven years while continuing with her professorial work. Her career has encompassed all areas of statistics, beginning as a mathematical statistician, progressing through all areas of applied statistics and currently involved in the broad field of Data Science.
Shirley is currently in her 44th year as a professor and has influenced the lives of many students, in many cases encouraging them to follow careers in statistics. She has received teaching awards from the University of Manitoba, the University of Winnipeg and from Carleton University. Shirley’s love of, and expertise in, teaching is demonstrated by the more than 80 graduate students that she has supervised – with many of them going on to international positions that involve significant statistical content. Her graduate course on Data Mining, started 20 years ago, foreshadowed the need for statisticians to work with massive data and to develop methodologies to handle it. This course has proven to be highly popular with students. Her course notes are widely in use and a co-authored book on this topic is currently in progress. In addition, she has co-authored several books concerned with public health issues of considerable importance. Her publication record includes many papers that reflect her interest in the application of statistics to societal issues of current relevance, for example, alcohol abuse, cannabis use, work-family stress, air pollution, privacy-preserving data mining.
Shirley has been active in the SSC in a wide variety of roles. Shirley’s involvement in SSC activities dates to the early 1970s when she helped to found the Statistical Association of Manitoba, a Regional Association of the SSC , and became its first Treasurer. In Ottawa she served on the Executive of another SSC regional association, the Statistical Society of Ottawa, as Secretary and as President. She was Executive Secretary of the SSC from 1990-94 and has also served as Secretary of the BISS Section of the SSC. Since 2011 she has been the Executive Director of the SSC and, in that position, has been instrumental in a number of key developments for the SSC. It is notable that Shirley has served as Executive Director of the SSC during the term of several Presidents, each of whom having asked her to continue in that role. She has been the SSC representative, and served as Chair, of the COPSS Committee for the Elizabeth Scott Award. She also served as the SSC representative to the Canadian Consortium on Research and has been, and continues to be, a member of numerous SSC committees.
Shirley’s distinguished service extends well beyond the SSC. She has a distinguished record of service to the statistical and wider academic community. At Carleton University she served as Salary Chair, as a member of the bargaining team, and as President of the Carleton University Academic Staff Association, was elected by the Science Faculty as their representative to Carleton’s Senate and was elected by Senate as its representative on the Carleton Board of Governors, where she served on its Executive, Audit, Nominating and University Relations committees. Currently she represents academic staff as a member of the University Pension Committee and serves on a number of other key university committees. During the Ontario Social Contract, she was Co-Chair of the Ontario Confederation of University Faculty Association’s Bargaining Team. During 1996-2002 she served as Treasurer on the Executive of the Canadian Association of University Teachers. She has also chaired the Canadian Section of the Caucus for Women in Statistics. She has headed the Co-op program in the School of Mathematics and Statistics at Carleton for many years and has been instrumental in matching students and employers. She has consulted widely for government and industry and played a number of roles in the Communications Security Establishment Canada (CSEC) and sister agencies. Throughout her career she has promoted statistics as a profession, worked for the accreditation of statisticians and served as a role model for women in statistics.
Recently the SSC established an office in Ottawa and hired its first staff person; Shirley was instrumental in facilitating this development. The establishment of the SSC office represents an important milestone as the size and complexity of SSC activities has become such that sole reliance on volunteers is no longer possible. In effect, the office will enable the SSC to better serve its members and help to develop the SSC’s voice for the statistical discipline and the profession in Canada.
Another key development for the SSC occurred during Shirley’s term as Executive Director. As a result of changes in federal legislation, in order for the SSC to continue as a not-for-profit organization in Canada, the SSC was required to adopt new Articles of Continuance (i.e. “new” Letters Patent) under which the SSC is incorporated and to do a complete re-write of the SSC Bylaws that govern the organization. The complexity involved in establishing compliance with not-for-profit legislation and with rules regarding charities was at times daunting and stressful for all involved, but Shirley handled this with admirable equanimity and a successful outcome was achieved. Her management of this process was well above what one might expect from a volunteer and demonstrates her dedication to the affairs of the SSC.
The citation for the award reads:
“To Shirley Mills, for important contributions to the SSC and the Canadian statistics community as Executive Director and Executive Secretary of SSC, SSC representative and Chair of the COPSS Committee for the Elizabeth Scott Award, Secretary of BISS, President of the Statistical Society of Ottawa; for service on numerous SSC committees over the span of four decades; for notable accomplishments during her term as Executive Director, and for a career of service and dedication to the development of statistics and statisticians in Canada.”
Pierre Robillard Award
Pierre Robillard Award: Ying Yan
Dr Ying Yan is the winner of the 2014 Pierre Robillard Award of the Statistical Society of Canada. This prize recognizes the best PhD thesis in probability or statistics defended at a Canadian university in a given year. Ying’s thesis is entitled “Statistical Methods on Survival Data with Measurement Error”. It was written at the University of Waterloo under the supervision of Grace Yi.
Ying’s PhD work focused on the analysis of survival data with measurement error. He developed a rich class of methods to correct for covariate error in additive hazards models, providing insightful and computationally compelling solutions. He proposed a general strategy to unify many existing methods and enhance our understanding of the available work in the literature. The issue of misspecification of the measurement error model is also addressed, with the identification of intrinsic conditions so that the developed testing procedures remain valid. Finally, Ying extended his research to the high-dimensional survival data regime, providing methods to perform simultaneous variable selection and parameter estimation.
Ying Yan was born in Qingyuan, China. He received a Bachelor of Science in Mathematics from the University of Science and Technology of China in 2008. Afterwards, he moved to the University of Waterloo, completing a Master of Mathematics in Statistics and a PhD in 2010 and 2014, respectively. As of September 2014 he is a Postdoctoral Fellow in the Department of Biostatistics at the University of North Carolina at Chapel Hill. He will move on in July 2015 to a position as an Assistant Professor in the Department of Mathematics and Statistics at the University of Calgary. His current research interests are survival and event history analysis, clinical designs (including biased sampling, case-cohort, case-control), measurement error and missing data, quantile regression and high-dimensional data analysis.
The criteria used in selecting the winner of the Pierre Robillard Award include the originality of ideas and techniques, the possible applications and their treatment, and the potential impact of the work. The award is named in memory of Professor Pierre Robillard, an outstanding dynamic young statistician at the Université de Montréal, whose untimely death in 1975 cut short what promised to be a highly distinguished career.
Ying Yan will present the results of his thesis in a special session at the 43rd Annual Meeting of the Statistical Society of Canada to be held in Halifax, Nova Scotia, June 14 to 17, 2015.
The certificate for the award reads:
“To Ying Yan, for the thesis entitled ‘Statistical Methods on Survival Data with Measurement Error’.”
CRM-SSC Prize in Statistics
CRM-SSC Prize in Statistics: Matías Salibián-Barrera
The CRM-SSC Prize in statistics is awarded annually by the Centre de recherches mathématiques (CRM) and the Statistical Society of Canada (SSC). It is awarded in recognition of a statistical scientist’s professional accomplishments in research during the first fifteen years after having received a doctorate. This year’s winner is Matías Salibián-Barrera of the University of British Columbia (UBC).
Matías Salibián-Barrera is one of the brightest and most accomplished young statisticians in our country. He was born in Chile and grew up in Buenos Aires, Argentina. He obtained his Bachelor in Mathematics at the University of Buenos Aires, where he was introduced to Statistics, and in particular to Robustness, by Victor Yohai – himself a major force in this field.
Matías’s doctoral dissertation was completed, in 2000, at UBC under the supervision of Ruben Zamar. The thesis, entitled Contributions to the Theory of Robust Inference, blends mathematical theory and computational procedures in a sophisticated manner that has continued throughout his career.
After graduation Matías was appointed Assistant Professor at Carleton University; after three years he returned in 2004 to UBC, where he is now Associate Professor. During his time at UBC he has also held Visiting Lectureships, designing and teaching short graduate level courses at Université libre de Bruxelles, Belgium, and at the University of Buenos Aires.
A remarkable feature of Matías’s research is that his contributions are not only rigorously documented in good papers but also implemented in statistical freeware. He is well known and prized in the statistical community for his non-trivial implementation of ‘state of the art’ robust methods in R. His methodological contributions include the fast and robust bootstrap, uniform asymptotics for robust location and regression estimates, globally robust inference, robust smoothing, and robust functional data analysis. Complementing this, his computational work includes fast S- and fast tau-regression estimates, deep involvement with the construction of the S-plus ‘robust’ library and the R-package ‘robustbase’, linear clustering, and robust and sparse k-means.
The fast and robust bootstrap introduced in Matías’s doctoral dissertation and subsequently developed in several joint papers with Stefan Van Aelst and Gert Willems represents a breakthrough in robust inference, by allowing the bootstrapping of robust methods. The straightforward application of the classical bootstrap to robust methods is not feasible because it does not yield robust inferences, and is much too slow. It has been adapted for numerous other scenarios, in particular for longitudinal studies and unbalanced clustering, by Alan Welsh (ANU) and collaborators.
Most proofs of asymptotic normality for robust procedures in the statistical literature use the unrealistic assumption of the validity of the central parametric model. This is unsatisfactory because robust methods are meant to be used with contaminated data. Matías’s research deals with this problem and has produced very strong results on the uniform consistency and asymptotic normality in a neighbourhood of the central parametric model. Matías’s introduction – jointly with Victor Yohai – of the fast regression S-estimator and the subsequent development of the fast tau-estimator are important breakthroughs for the efficient computation of these regression estimates. Similar ideas have also been used to compute multivariate location estimators.
More recently, Matías has turned his attention to functional principal component analysis. Dimension reduction associated either with variable selection in regression or the approximation of covariance matrices is an essential part of addressing the problems associated with high-dimensional data analysis. In a recent JASA paper Matías studies ways to find lower dimensional approximations which fit the functional data well and have minimum prediction error.
Matías’s contributions to the profession go beyond his research. In service to the SSC he has served on the local organizing committee for the 2009 meeting in Vancouver and on the SSC Board. He has been a wonderful colleague in the Department of Statistics at UBC whose members, beyond pointing to his various research contributions, also emphasize his generous contributions to the department and the discipline. Matías is a valued Associate Editor for both The Canadian Journal of Statistics and Computational Statistics and Data Analysis.
Matías and his wife Veronica have been very busy raising three children. Matías enjoys hiking and learning photography. On a typical fall or winter evening you can find him at the soccer pitch, either coaching one of his sons or playing for one of his two teams. He enjoys a wide range of music styles, and will rarely miss a concert of his favourite Canadian band: Rush.
Matías Salibián-Barrera will present an overview of his work in a special session at the 43rd Annual Meeting of the Statistical Society of Canada to be held in Halifax, Nova Scotia, June 14 to 17, 2015.
The citation for the prize reads:
“To Matías Salibián-Barrera for his fundamental contributions to the field of robust statistics, for the introduction of influential new methodology such as the fast and robust bootstrap and the fast S-estimator for robust regression, and for his breakthrough innovations in efficient computational algorithms for robust procedures.”
The Canadian Journal of Statistics Award
The Canadian Journal of Statistics Award: Douglas E. Schaubel, Hui Zhang, John D. Kalbfleisch and Xu Shu
Doug Schaubel |
Hui Zhang |
John D. Kalbfleisch |
Xu Shu |
The Canadian Journal of Statistics Award is presented each year by the Statistical Society of Canada to the author(s) of an article published in the Journal, in recognition of the outstanding quality of the methodological innovation and presentation. This year’s winner is the article entitled “Semiparametric methods for survival analysis of case-control data subject to dependent censoring” (Volume 42, no. 3, pp. 365-383) by Douglas E. Schaubel, Hui Zhang, John D. Kalbfleisch, and Xu Shu.
In case-control sampling, subjects are selected into the study based on the outcome of interest. It was established long ago that proportional hazards regression can be applied to case-control data. However, each of the various estimation techniques available assumes that failure times are independently censored, an assumption often violated in observational studies. This paper proposes and analyzes methods for Cox regression analysis of survival data obtained through case-control sampling, but subject to dependent censoring. The methods are based on weighted estimating equations, with separate inverse weights used to account for the case-control sampling and to correct for dependent censoring. The proposed estimators are shown to be consistent and asymptotically normal, and consistent estimators of the asymptotic covariance matrices are derived. The methods are illustrated through an analysis of pre-transplant mortality among end-stage liver disease patients obtained from a national organ failure registry.
Doug Schaubel is a Professor of Biostatistics at the University of Michigan. He holds a PhD in Biostatistics from the University of North Carolina at Chapel Hill. His methodological research interests focus on survival analysis and recurrent event data. His collaborative work is largely motivated by issues arising in organ failure and transplantation, settings which feature complex data structures and censoring patterns not amenable to standard techniques. Doug collaborates with members of the University of Michigan Kidney Epidemiology and Cost Center (KECC) and Arbor Research Collaborative for Health. Doug previously won the CJS Award in 2008 with co-author Qing Pan.
Hui Zhang received her PhD in 2011 from the Department of Biostatistics at the University of Michigan. Prior to her arrival at Michigan, Hui received a Master’s in Statistics from the Colorado State University, and a Bachelor of Economics from the University of Science and Technology of China. Hui’s dissertation developed methods for case-control and clustered case-cohort data. Her work as a research assistant included analyzing end-stage renal disease registry data from Canada and the United States. Since graduating from Michigan, Hui has worked at the U.S. Food and Drug Administration; she is currently a Statistical Reviewer, with a primary focus on oncology drugs.
John D. Kalbfleisch is Professor Emeritus of Biostatistics and Statistics at the University of Michigan and Distinguished Professor Emeritus at the University of Waterloo. Jack received his Ph.D. in statistics in 1969 from the University of Waterloo. Before going to Michigan in 2002, he was at the State University of New York at Buffalo (1970-73) and at the University of Waterloo (1973-2002) where he was Chair of the Department of Statistics and Actuarial Science (1984-1990) and the Dean of the Faculty of Mathematics (1990-1998). His wide interests include life history and survival analysis, likelihood methods of inference, mixture and mixed effects models, and medical applications, particularly in the area of renal disease and organ transplantation.
Xu Shu is a Ph.D candidate at the University of Michigan Department of Biostatistics, where she obtained a Master of Science (Biostatistics) in 2012. Xu’s undergraduate work was completed at Beijing Normal University, where she majored in Statistics. Xu’s dissertation develops novel semiparametric methods for comparing gap times (i.e., times between successive events). As part of her work as a research assistant, Xu has analyzed kidney, liver and multi-organ transplant data obtained from a national organ failure registry. Methods developed in her dissertation were motivated by this database. She has also worked as a research assistant at the Center for Statistical Genetics. Xu is scheduled to complete her dissertation during the summer of 2015.
The award-winning paper will be presented by Doug Schaubel in a special session at the 43rd Annual Meeting of the Statistical Society of Canada to be held in Halifax, Nova Scotia, June 14 to 17, 2015.
The certificate for the award reads:
“To Douglas E. Schaubel, Hui Zhang, John D. Kalbfleisch, and Xu Shu for excellence, innovation and presentation in the article entitled “‘Semiparametric methods for survival analysis of case-control data subject to dependent censoring’.”
SSC Impact Award
SSC Impact Award: Shelley Bull
The 2015 recipient of the Statistical Society of Canada Award for Impact of Applied and Collaborative Work is Shelley Bull, Senior Investigator in the Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital and Professor in the Division of Biostatistics, Dalla Lana School of Public Health at the University of Toronto. The award recognizes outstanding contributions by members of the SSC in collaborative research and applied work, the importance of which derives primarily from its relatively recent impact on a subject area outside of the statistical sciences, on an area of application, or on an organization.
Born in Hamilton Ontario, Shelley grew up in Burlington and Etobicoke in southern Ontario. She obtained BMath (1976) and MMath (1977) degrees at the University of Waterloo where faculty members in the Department of Statistics and Actuarial Sciences fostered her interests in biostatistics and applied work. Following doctoral and post-doctoral work in the Department of Epidemiology and Biostatistics at the University of Western Ontario (1978-86), completed under the supervision and mentorship of Allan Donner, Shelley joined the Clinical Epidemiology Group in the newly-created Research Institute at Mount Sinai Hospital, Toronto and was appointed as Assistant Professor in the Department of Preventive Medicine and Biostatistics, University of Toronto. There she developed an independent research program focused on categorical data modeling in epidemiology, continued collaborations in population-based surveys of attitudes towards anti-smoking measures, and initiated new collaborations in the molecular genetics of breast cancer. In the mid-1990’s, with the advent of new molecular technologies and international initiatives such as the Human Genome Project, Shelley began to work more intensively on problems in statistical genetics and molecular and genetic epidemiology, taking on leadership in the development of a multi-institution research group in Toronto which expanded into a national research team as part of the Network of Centres of Excellence in Mathematics (MITACS), and in the establishment of a University of Toronto interdisciplinary training program in Genetic Epidemiology and Statistical Genetics (CIHR STAGE, with F. Gagnon).
Her excellence as a statistical scientist working in epidemiology and biostatistics has been recognized by multiple research awards: doctoral and postdoctoral awards from the National Health Research Development Program (NHRDP 1979-83) and the Ontario Ministry of Health (1983-85) respectively, a National Health Research Scholar Award (1989-99), and a Canadian Institutes of Health Research (CIHR) Senior Investigator Award (2002-07). She is also a recipient of The Anthony Miller Award For Excellence in Research In Public Health, Graduate Department of Public Health Sciences, University of Toronto (2001), the Genetic Epidemiology Best Paper Award from the International Genetic Epidemiology Society (2002, with Darlington, Greenwood, Shin), and the International Genetic Epidemiology Society Leadership Award (2012).
Shelley has authored or co-authored over 180 peer-reviewed research papers and book chapters encompassing statistical methods and their applications in population and public health; in perinatology, nephrology and rheumatology; and in molecular cancer genetics, molecular and genetic epidemiology, human genetics, and statistical genetics. This work reflects the synergistic relationship between her basic biostatistical and applied research programs, typified by the concurrent application of innovative statistical methods to bear on substantive scientific questions, with the identification of gaps in statistical methodology and the need for new methods motivated by collaboration with colleagues from other disciplines and their understanding of current scientific approaches. Over the years, Shelley has made the training of graduate students and post-doctoral fellows in statistical research methods and interdisciplinary collaborative research increasingly integral to her research program. She credits her collaborations with trainees and colleagues, both statistical and non-statistical, as a wonderful source of intellectual stimulation that has contributed largely to her understanding of statistical, biomedical, and epidemiological science.
Her interest in methods for categorical data analysis, beginning with doctoral and post-doctoral work in large sample efficiency of multinomial logistic regression, found expression in an early application of GEE to multiple categorical outcomes in large observational studies and in extensions of affected sib pair genetic linkage methods to account for heterogeneity by use of covariates. Involving a number of graduate students and post-doctoral fellows, Shelley’s group also developed new approaches for practical inference under a penalized multinomial likelihood particularly useful with sparse data. Their findings are relevant to genetic association analysis of low frequency and rare variants now being generated by next generation sequencing technologies and to the study of multiple traits with shared genetic determinants.
In a long-term collaboration with molecular geneticist
Dr. Andrulis of the Lunenfeld-Tanenbaum Research Institute, Shelley’s work addressed the design and analysis of studies to investigate the role of molecular genetic alterations in tumour biology and risk of metastasis. Early investigations of selected DNA alterations in breast cancer tumours revealed molecular interactions and time-dependent associations with early metastasis-free survival in a large prospective cohort of patients. Subsequent challenges in analyses of unselected genomic markers, measured using microarrays that quantify RNA gene expression or DNA alterations, led post-doctoral statistical research fellows within the group to develop methods to effectively analyse and integrate high-dimensional tumour measurements. The establishment of tissue microarrays (TMAs) to measure tumour protein expression in the cohort further stimulated implementation of advanced statistical methods. In particular, application of mixture-cure models capable of modeling both early and long-term molecular associations with risk of metastasis led to novel insights and helped explain counter-intuitive results obtained by standard methods. She anticipates on-going work to focus increasingly on integration of multiple molecular features for understanding of biological mechanisms.
The development of statistical methods for the detection, localization and characterization of susceptibility genes associated with complex traits and diseases by means of genetic analysis of genotyping and sequencing data collected from extended pedigrees, small families and unrelated individuals is a major focus of Shelley’s research program. Graduate students and post-doctoral fellows working with Shelley and colleagues have developed and evaluated complementary types of statistical genetic analysis including models that relate genetic similarity among relatives to functions of their trait values and other measurable characteristics, as well as methods to integrate data from parent-offspring trios and unrelated individuals, and models for regional/gene-based analysis and for multiple correlated traits in unrelated individuals. These methods were applied in genetic studies of inflammatory bowel disease, kidney stone disease, arthritis, hypertension, diabetes, blood pressure, and blood lipids. Motivated by the wide adoption of high-density genotyping technologies and associated concerns about the reliability of genetic effect detection and estimation in the face of high-dimensional multiple testing, Shelley and collaborators developed a general non-parametric bootstrap resampling method to address the upward bias in genetic effect estimation resulting from the application of stringent criteria for statistical significance to control false positive findings. Bias-reduced estimates are helpful in interpretation and in power considerations for replication study design. Resampling-based estimators are attractive because they require only specification of well-defined parameter estimation and hypothesis testing procedures, and are broadly useful for quantitative, binary and time-to-event traits. Recent work is exploring approaches to multi-phase, multi-stage, and trait-dependent sampling design and analysis to improve cost-efficiency by limiting the use of expensive molecular technologies to more informative individuals.
A second area of scientific collaboration has focused on the discovery of genetic determinants for complications of type 1 diabetes, building on infrastructure designed to follow participants of a pivotal randomized trial of alternate modes of insulin delivery. Led by geneticist Dr. AD Paterson, Hospital for Sick Children Research Institute, the group has conducted genome-wide association studies of a number of complex traits, including time to kidney and eye complications, blood sugar levels, cardiovascular risk factors, kidney function, and related traits. These studies, based on high-density sets of genetic susceptibility variants and longitudinal measurements of traits over extended follow-up, have motivated the development of new statistical methods by post-doctoral fellows and graduate students, and served as a testing ground for the evaluation and application of bias-reduced estimation, gene-based test statistics, and joint association models for longitudinal traits and time-to-event outcomes.
Shelley has also contributed to collaborative and applied research at a broad level through her work as an Associate Editor for the American Journal of Epidemiology (1991-98), The Canadian Journal of Statistics (2007-13), and Statistics in Medicine (2010 to present), as well as by service on grant review panels for NHRDP Doctoral Training Awards, CIHR Population Health Operating Grants, National Cancer Institute (Canada) Molecular, Environmental and Lifestyle Cancer, CIHR Genetics Operating Grants, and as grant reviewer for NSERC and other national and international agencies. She has served on the Board of Directors of the International Genetic Epidemiology Society, member and co-Chair of the Joint Priorities and Planning Committee in Genetic Epidemiology for the CIHR Institutes of Genetics and Population and Public Health, and is currently a member of the Advisory Committee to the Genetic Analysis Workshop funded by the US NIH.
An SSC member since her graduate student days, Shelley has served as Regional Representative on the Board of Directors (1989-91), Secretary of the Biostatistics Section (1992-95), Program Chair of the SSC Annual Meeting at Acadia University (2011), and as member on various SSC Committees.
Shelley lives in downtown Toronto with her husband, Wayne, who was a fellow undergraduate in residence at the University of Waterloo Conrad Grebel College. On weekends they attend to a 130-year-old farmhouse in rural Wellington County, which involves planting trees, weeding gardens, sometimes harvesting vegetables and, occasionally, reading in the shade.
The citation for the award reads:
“To Shelley Bull, for her outstanding contributions to research in medicine, public health, genetics and epidemiology; for the development of statistical methodology for these areas; and for her leadership, supervision, and mentorship in the Canadian statistical genetics and genetic epidemiology communities.”