CHANCE is copublished quarterly by the American Statistical Association and Taylor & Francis Group. The magazine is designed for anyone who has an interest in using data to advance science, education, and society. CHANCE is a non-technical magazine highlighting applications that demonstrate sound statistical practice. CHANCE represents a cultural record of an evolving field, intended to entertain as well as inform.
Since its creation in 1988, CHANCE has covered such topics as the 1990 census adjustment and the redesigned population survey, sports, the environment, DNA evidence in the courts, a variety of medical issues—even how to win on “Jeopardy.” CHANCE offers a unique opportunity to reach beyond statistics professionals to a more general audience.
Scott Evans is a senior research scientist at Harvard University, where he is the director of the Statistical and Data Management Center for the Antibacterial Resistance Leadership Group and teaches clinical trials. He’s received the Robert Zackin Distinguished Collaborative Statistician Award for significant statistical contributions to HIV research and a recognition award from the Harvard School of Public Health IRB. He is also a Fellow of the American Statistical Association (ASA). Evans is a member of an FDA advisory committee and has served on and chaired numerous data monitoring committees and scientific advisory committees. He is the past president of the ASA Boston Chapter, past chair of the ASA Development Committee, past chair of the ASA Teaching Statistics in the Health Sciences and Statistics in Sports sections, and member of the board of directors for Mu Sigma Rho, the National Honorary Society for Statistics.
Sam Behseta earned his PhD from Carnegie Mellon University and is a professor at California State University, Fullerton. His main research area is statistics in neuroscience. Other research interests include stochastic modeling of decisionmaking with multi-alternatives, Bayesian functional data analysis, Bayesian nonparametrics, statistical modeling of epidemiological data, and probabilistic watermarking. Behseta has trained and mentored undergraduate and graduate students.
Michael Larsen earned his PhD in statistics from Harvard University and is associate professor of statistics at George Washington University in Washington, DC. He has been on the faculty at Iowa State University and The University of Chicago and worked as a consultant with the U.S. Census Bureau, the U.S. National Center for Health Statistics, NORC, and the Gallup Organization, Inc. His research interests include survey sampling, missing data, record linkage, statistical modeling, applied statistics, and statistics education.
Dalene Stangl is professor of the practice of statistics and public policy and associate chair of the Department of Statistical Science at Duke University in North Carolina. She is reviews editor of the Journal of the American Statistical Association and The American Statistician and has co-authored more than 100 articles in statistics, as well as contributed substantive research to journals in medicine and health policy. Her professional interests are hierarchical models, meta-analysis, decision analysis, and the reform of statistical education and statistical practice.
Michael Lavine was a professor of statistics at Duke University from 1987 through 2008 and is now professor of statistics and director of the Statistical Consulting and Collaboration Center at UMass Amherst. He is author of the free graduate-level text Introduction to Statistical Thought. He has wide interests in statistical methodology and applications and is Subject Matter Editor for statistical articles in Ecology and Ecological Monographs.
Hal S. Stern is Ted and Janice Smith Family Foundation Dean of the Donald Bren School of Information and Computer Sciences and professor of statistics at the University of California, Irvine. Prior to becoming dean, he was founding chair of the department of statistics at UC Irvine and held faculty positions at Iowa State University and Harvard University. His research interests include assessing the fit of statistical models, combining information using Bayesian methods, applications of statistics in the social and biological sciences, and statistics in sports. He has authored more than 80 refereed journal publications and is co-author of the graduate-level statistics text Bayesian Data Analysis. He is a Fellow of the American Statistical Association and Institute of Mathematical Statistics.
Jim Albert is professor of statistics in the department of mathematics and statistics at Bowling Green State University. He is the author of Bayesian Computation with R and coauthor of the books Curve Ball, Ordinal Regression Modeling, R by Example, and Analyzing Baseball with R. His interests include Bayesian modeling, statistics education, and the application of statistical thinking in sports. He has been editor of The American Statistician and Journal of Quantitative Analysis in Sports and he is a Fellow of the American Statistical Association.
Dean Follmann is head of the Biostatistics Research Branch of the National Institute of Allergy and Infectious Diseases and an ASA Fellow. He earned his PhD in statistics from Carnegie Mellon University. Current research interests include counterfactual models, vaccine development, and immunology.
Toshimitsu (Toshi) Hamasaki is chief of the Office of Biostatistics and Data Management at the National Cerebral and Cardiovascular Center in Japan. He has served as editor-in-chief of the Journal of the Japanese Society of Computational Statistics and is currently an associate editor for the Japanese Journal of Applied Statistics, Journal of the Japanese Society of Computational Statistics, and Statistics in Biopharmaceutical Research. Hamasaki is an elected member of International Statistical Institute and was awarded the Distinguished Article Award from the Japanese Society of Computational Statistics and Hida-Mizuno Prize from the Behaviormetric Society of Japan. His research interests focus on issues in the design and analysis of clinical trials with multiple objectives, including multiple endpoints, targeted subgroup populations, adaptive/group-sequential designs, and noninferiority-superiority.
Jo Hardin is an associate professor at Pomona College in Claremont, California. Her research interests include outlier detection, clustering, and robust methods, particularly applied to large data sets. Recently, she has worked on microarray data, creating similarity measures for determining coexpression of genes. Outside of work, she enjoys reading, running, and breeding tortoises.
Nicholas Horton is a professor of statistics at Amherst College in Massachusetts. His research interests are in longitudinal regression models and missing data methods, with applications in psychiatric epidemiology and substance abuse research.
Tom Lane earned his PhD at MIT and is a statistician at MathWorks, where he manages development for the MATLAB Statistics Toolbox. He formerly developed statistical software while at Domain Manufacturing Corporation, BBN, and IBM Research.
Mary Meyer is originally from Chicago and earned her PhD from the University of Michigan. She is currently associate professor of statistics at Colorado State University at Fort Collins. Her research interests are in nonparametric function estimation and inference methods using shape restrictions.
Michael McDermott is a professor of biostatistics and neurology and a professor in the Center for Human Experimental Therapeutics at the University of Rochester School of Medicine and Dentistry. He is also associate chair of the department of biostatistics and computational biology and director of graduate studies for the department. He has been a leading member of several national and international collaborative groups conducting clinical research in neurological disease, neuro-ophthalmological disorders, and pain. He is a former associate editor of the journal Neurology and is on the editorial board of the journal Movement Disorders. His research interests include order-restricted inference, receiver operating characteristic (ROC) curves and surfaces, missing data problems, meta-analysis, and clinical trials methodology.
Kary Myers earned her degrees from Carnegie Mellon University while working on projects ranging from galaxy clusters to speech recognition to neuroimaging. As a scientist at Los Alamos National Laboratory, she applies statistical and machine learning techniques to time series data in the context of remote sensing (not to be confused with remote viewing).
Babak Shahbaba is assistant professor of biostatistics at the University of California, Irvine, where he has been teaching undergraduate courses such as Introduction to Biostatistics and graduate courses such as Advanced Statistical Methods and Bayesian Analysis. His research interest is related to developing novel statistical methods to answer research questions in genomics, proteomics, and cancer studies.
Lu Tian holds a bachelor’s degree in mathematics from Nankai University, master’s degree in applied mathematics from Nankai University, and doctor of science degree in biostatistics from Harvard University. His graduate study was supported by a Howard Hughes Fellowship and he was awarded the Robert B. Reed Award for Excellence in Biostatistics at Harvard University. He is associate professor in the department of health research and policy at Stanford University. Tian has rich experience in conducting statistical methodological research, planning large epidemiological studies, running data management for randomized clinical trials, and conducting applied data analysis. His current research interest is in developing statistical methods in semiparametric regression modeling, survival analysis, and high-throughput data analysis.
Dianne Cook who writes the Visiphilia column, is a professor of statistics at Iowa State University and an ASA Fellow. Her primary research interest is on visualizing data using interactive graphics. She earned her PhD from Rutgers University in 1993, while working closely with researchers at Bellcore, on grand tour and projection pursuit methods, implemented in the software XGobi. At ISU, she teaches data mining, multivariate analysis, data technologies, and introductory statistics, and she works with graduate students in the Human Computer Interaction program and bioinformatics and computational biology programs.
Andrew Gelman, is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. He has received many awards, including the Outstanding Statistical Application Award from the American Statistical Association and the award for best article published in the American Political Science Review. He has coauthored many books; his most recent is Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do.
Mary Gray, who writes The Odds of Justice, is professor of mathematics and statistics at American University in Washington, DC. Her PhD is from the University of Kansas, and her JD is from Washington College of Law at American. A recipient of the Elizabeth Scott Award from the Committee of Presidents of Statistical Societies, she is currently chair of the American Statistical Association Scientific and Public Affairs Advisory Committee. Her research interests include statistics and the law, economic equity, survey sampling, human rights, education, and the history of mathematics.
Shane T. Jensen, who writes A Statistician Reads the Sports Pages, is an associate professor of statistics in the Wharton School at the University of Pennsylvania, where he has been teaching since completing his PhD at Harvard University in 2004. Jensen has published more than 40 academic papers in statistical methodology for a variety of applied areas, including molecular biology, psychology, and sports. He maintains an active research program in developing sophisticated statistical models for the evaluation of player performance in baseball and hockey.
Nicole Lazar, who writes The Big Picture column, earned her PhD from The University of Chicago. She is a professor in the department of statistics at the University of Georgia, and her research interests include the statistical analysis of neuroimaging data, empirical likelihood and other likelihood methods, and data visualization. She also is an associate editor of The American Statistician and The Annals of Applied Statistics and the author of The Statistical Analysis of Functional MRI Data.
Christian Robert is a professor of statistics at Université Paris-Dauphine and a senior member of the Institut Universitaire de France. He has authored eight books and more than 150 papers on applied probability, Bayesian statistics, and simulation methods. Robert also served as joint editor of the Journal of the Royal Statistical Society Series B and associate editor for most major statistical journals. He is a fellow of the Institute of Mathematical Statistics and the recipient of an IMS Medallion.
Aleksandra Slavkovic, who writes O Privacy, Where Art Thou?, earned her PhD from Carnegie Mellon University. She is an associate professor of statistics, with appointments in the department of statistics and Institute for CyberScience at Penn State University and department of public health sciences at Penn State College of Medicine. She serves as an associate editor of the Annals of Applied Statistics, Journal of Privacy and Confidentiality, and Journal of Statistical Computation and Simulation. Her primary research interest is in data privacy and confidentiality. Other research interests include evaluation methods for human performance in virtual environments, statistical data mining, application of statistics to social sciences, algebraic statistics, and causal inference.
Dalene Stangl is professor of the practice of statistical science and public policy and associate chair of the department of statistical science at Duke University in North Carolina. She has served in editorial positions for the Journal of the American Statistical Association, The American Statistician, and Bayesian Analysis and has co-edited two books with Donald Berry, Bayesian Biostatistics and Meta-Analysis in Medicine and Health Policy. Her primary interest is promoting Bayesian ideas in the reform of statistics education and statistical practice.
Mine Çetinkaya-Rundel is an assistant professor of the practice at Duke University. Her research interests include statistics pedagogy, spatial statistics, small-area estimation, and survey and public health data. She is a co-author of OpenIntro Statistics and a contributing member of the OpenIntro project, whose mission is to make educational products that are open-licensed, transparent, and help lower barriers to education.
Howard Wainer, who writes Visual Revelations, is currently distinguished research scientist at the National Board of Medical Examiners and professor of statistics at the Wharton School, University of Pennsylvania. He has won numerous awards and is a Fellow of the American Statistical Association and the American Educational Research Association. His interests include the use of graphical methods for data analysis and communication, robust statistical methodology, and the development and application of generalizations of item response theory. He has published many books; his latest is The Second Watch: Navigating an Uncertain World.