Xiao-Li Meng
Author Archives: Sharon
Multiple Test Procedures with Gatekeeping and Graphical Applications
Instructor: Ajit C. Tamhane (Northwestern University)
AUGUST 18, 8:30—Noon
ROOM: LInC 368
Modern phase III confirmatory clinical trials often involve multidimensional study objectives which require simultaneous testing of multiple hypotheses with logical relationships among them. Examples of such study objectives include investigation of multiple doses or regimens of a new treatment, multiple endpoints, subgroup analyses, non-inferiority and superiority tests, or any combination of these. This short course will provide practical guidance on how to construct multiple testing procedures (MTPs) for such hypotheses while taking into account the logical relationships among them and controlling the appropriate Type I error rate. Continue reading
Katherine Ensor
Professor and Chair of Statistics in the School of Engineering and Director of CoFES, Rice University
Keynote Speaker
Debashis Ghosh
Department Chair for Biostatistics & Informatics, Colorado School of Public Health
Keynote Speaker
Kannan Natarajan
Senior Vice President and Global Head of Biometrics and Data Management, Novartis
Keynote Speaker
Ajit Tamhane
Senior Associate Dean (Graduate Studies and Planning), McCormick School of Engineering and Applied Science
Keynote Speaker
Statistical Computing with Julia
Instructor: Hua Zhou (University of California, Los Angeles)
AUGUST 18, 8:30—Noon
ROOM: LInC 268
Julia is a new open source programming language for technical computing. Its flexible design offers greater speed and power than the R+Python combination without radical change. Are statisticians and data scientists ready for Julia and is Julia ready for them? This short course illustrates the basic language features, numerical linear algebra, statistical functions (JuliaStat), optimization (JuliaOpt), and parallel and distributed computing in Julia using a variety of statistical applications. Continue reading
Bayesian Computation using PROC MCMC
Instructor: Fang Chen (SAS Institute Inc)
AUGUST 18, 1:30—5 PM
ROOM: LInC 268
The MCMC procedure is a general purpose Markov chain Monte Carlo simulation tool designed to fit a wide range of Bayesian models, including linear or nonlinear models, multi-level hierarchical models, models with nonstandard likelihood function or prior distributions, and missing data problems. This tutorial starts with an in-depth introduction to PROC MCMC and moves on to demonstrate its use with a series of applications. An optional and brief introduction to Bayesian and MCMC methods is included if the audience prefers an overview on the paradigm. Continue reading
Debashis Mondal, Lead Organizer
IISA 2016 Program Committee
Debashis Mondal, Oregon State University
N. Balakrishnan, Mcmaster University
Sujit Ghosh, North Carolina State University
Ginny Lesser, Oregon State University
Tapan Nayak, George Washington University
Aarti Singh, Carnegie Mellon University
Satrajit RoyChoudhury, Novartis
Abdus S Wahed, University of Pittsburg
Helen Zhang, Arizona State University