ICSA 2009 APPLIED STATISTICS SYMPOSIUM

June 21st-24th, San Francisco, California, USA

Keynote Speech

Title	Abstract	About the Speaker
Alternatives to Intention to Treat—the MIRA Trial	The application of standard randomized clinical trial methodology to large-scale intervention trials presents a number of challenges in design, analysis and interpretation. As motivation, consider The Methods for Improving Reproductive Health in Africa (MIRA) trial, a recently completed randomized trial that investigated the effect of diaphragm and lubricant gel use in reducing HIV infection among susceptible women. 5,045 women were randomly assigned to either the active treatment arm or not. Additionally, all subjects in both arms received intensive condom counseling and provision, the “gold standard” HIV prevention barrier method. There was much lower reported condom use in the intervention arm than in the control arm, making it difficult to answer important public health questions based solely on a standard intention-to-treat analysis. This presentation will explore these issues and describe an analysis technique adapted from causal inference to estimate the “direct effects” of assignment to the diaphragm arm, adjusting for condom use in an appropriate sense. The impact of measurement error will also be considered and attempts to allow for non-compliance to the assigned treatment. Questions raised by the MIRA trial apply to other HIV prevention trials currently being conducted or designed.	Nicholas P. Jewell is Professor of Biostatistics and Statistics at the University of California, Berkeley. He has held various academic and administrative positions at Berkeley since his arrival in 1981, most notably serving as Vice Provost from 1994 to 2000. He was trained at the University of Edinburgh where he received an Honours degree in Applied Mathematics in 1973 and a PhD in Mathematics in 1976. Immediately following his graduate program, he was appointed to a Harkness Fellowship from 1976-1978 which he held at the University of California, Berkeley and at Stanford University. From 1979-1981 he was an Assistant Professor of Statistics at Princeton University. He has also held academic appointments at the University of Edinburgh and at Oxford University. Jewell is a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science (AAAS). He is the 2005 winner of the Snedecor Award from COPSS, and won the Distinguished Teaching Award from UC Berkeley's School of Public Health in 2004. In 2000, he was awarded the Director's Award from the Federal Emergency Management Agency for "extraordinary leadership and vision in implementing strategies that enhance the disaster resistance of the University of California, Berkeley, and universities throughout America"; in addition the 2005 Alfred E. Alquist Award was given to UC Berkeley's SAFER program that he launched and led for many years. In 2007, he was a Fellow at the Rockefeller Foundation Bellagio Center in Italy. Jewell worked originally in functional analysis before turning to Biostatistics. He has made major contributions to statistical techniques for the analysis of epidemiological data, longitudinal data analysis, and survival analysis--particularly current status data. In applications, he has worked on HIV and AIDS data since the beginning of the epidemic in 1981, and more recently on other infectious diseases, and in environmental epidemiology and vision science, publishing more than 120 research articles. Jewell has had more than 20 Ph.D. students at Berkeley and has been an Associate Editor of Biometrika, The Journal of the American Statistical Association, The Annals of Statistics, The International Statistical Review, The American Statistician, and Statistical Science. In addition, he was a founding Editor of Lifetime Data Analysis. At bepress, he launched two journals, Statistical Applications in Genetics and Molecular Biology and The International Journal of Biostatistics, for which he is still Senior Editor. He is the author of the monograph, Statistics for Epidemiology, published by CRC Press. He is a past President of the WNAR region of the Biometric Society, Treasurer of IMS, and member of the National Research Council's Committees on National Statistics and on Applied and Theoretical Statistics.
Some statistical issues in the analysis of next generation sequence data	One of the most exciting recent developments in biology has been the advent of sequencing technology capable of producing many billions of bases of sequence information in a single run. In this talk I will examine some of the statistical issues related to the application of this technology to the study of gene expression and gene regulation. I will review some of the problems where significant progresses have already been made, such as the mapping of sequence reads and the computation of gene-level expression indexes. I will also discuss some problems that may require further research, such as the modeling of paired sequence reads, the estimation of isoform-specific expression, and the discovery of novel transcripts.	Wing Hung Wong, Professor, Department of Health Research and Policy and Department of Statistics, Stanford University, CA Professor Wong received his BA in Mathematics and Statistics from the University of California at Berkeley (1976), MS in Statistics (1978) and Computer Sciences (1980), and Ph.D. in Statistics (1980) from the University of Wisconsin at Madison. He was Assistant (1980-1985), Associate (1985-1988) and Full Professor (1988-1994) of Statistics at the University of Chicago. From 1994 to 1997, he was the Associate Director of the Institute of Mathematical Sciences and Professor and Chairman of the Department of Statistics at the Chinese University of Hong Kong. He was Professor of Statistics at University of California, Los Angeles, from 1997 to 2000, and was Professor of Statistics and Biostatistics at Harvard University from 2000 to 2004. In 2004, he moved to Stanford University, where he leads a laboratory to develop methods and software for the analysis of data from high-throughput genomics studies. He will be Chair of the Stanford Department of Statistics in September, 2009. Professor Wong has made many seminal contributions to statistical theory and the biomedical sciences. His is well known to the statistical community for his contributions in data augmentation, Monte Carlo, and Bayesian methods. He has also made major contributions to computational biology and system biology. He has published more than 120 peer-reviewed scientific papers and is one of the most cited mathematicians in the world. His scientific achievements have won him many prestigious awards and honors. He is a fellow of IMS, ASA, AAAS, and an elected member of ISI. He won the COPSS award in 1993 and was recently elected to the US National Academy of Sciences. He served as associate editor for JASA, Annals of Statistics, Statistica Sinica, IEEE/ACM,and is on the editorial board of Journal of Computational Biology and Annals of Applied Statistics. Professor Wong is the advisor of 22 Ph.D. students, many of whom have become leaders of statistical sciences.
Challenges and Opportunities for the Statistics Profession and for Professional Statistical Societies	Banquet Keynote Speech, 7PM, June 23, 2009, Tuesday	Ron Wasserstein is Executive Director of the American Statistical Association.  Prior to joining the ASA staff, Ron was a faculty member and administrator for 23 years at Washburn University, serving the last seven years as the University's chief academic officer.  During his years at Washburn, Ron was deeply involved in the ASA as a volunteer, having served in numerous positions, including on the Board of Directors.  In 2003, he was named a Fellow of the ASA.