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Présentation New Developments In Statistical Modeling, Inference And Application Format Relié
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Résumé :
The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking, and innovative clinical trial design and analysis. Each paper was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. It offered 3 keynote speeches, 7 short courses, 76 parallel scientific sessions, student paper sessions, and social events.
Biographie: Zhezhen Jin, Ph.D., is Professor of Biostatistics in the Department of Biostatistics, Mailman School of Public Health, Columbia University. He is a Fellow of the American Statistical Association. His research interests include survival analysis, resampling methods, longitudinal data analysis, and nonparametric and semiparametric models. Dr. Jin has collaborated on research in the areas of cardiology, neurology, cancer and epidemiology and is co-founding editor of Contemporary Clinical Trials Communications. Mengling Liu, Ph.D., is Associate Professor and Interim Director of the Division of Biostatistics in the Department of Population Health and the Department of Environmental Medicine at the New York University School of Medicine. Dr. Liu's research interests include semiparametric modeling and inference for survival data, joint analysis with longitudinal data, statistical genetics, statistical modeling in epidemiology studies andother types of risk-set sampling studies. She is engaged in a broad range of collaborative projects in the area of cancer epidemiology, pulmonary disease, cardiovascular disease, and environmental health science. Xiaolong Luo, Ph.D., is Senior Director of Statistics with Celgene Corporation. Dr. Luo has many years of experience in the design, conduct, and analysis of clinical trials. Prior to joining Celgene, he was a Director of Statistics with Johnson & Johnson and a Senior Research Biostatistician with Bristol-Meyers Squibb. He served as a faculty member at St. Jude Children's Research Hospital before joining industry.
Sommaire: Part I: Theoretical Development in Statistical Modeling 1. Dual Model Misspecification in Generalized Linear Models with Error in Variables Xianzheng Huang 2. Joint Analysis of Longitudinal Data and Informative Observation Times with Time-Dependent Random Effects Yang Li, Xin He, Haiying Wang and Jianguo Sun 3. A Markov Switching Model with Stochastic Regimes with Application to Business Cycle Analysis Haipeng Xing, Ning Sun and Ying Chen 4. Revisiting Regression Analysis under Link Violation Yuexiao Dong and Zhou Yu Part II: New Developments in Trial Design 5. Futility Boundary Design Based on Probability of Clinical Success under New Drug Development Paradigm Yijie Zhou, Ruji Yao, Bo Yang and Ramachandran Suresh 6. Bayesian Modeling of Time Response and Dose Response for Predictive Interim Analysis of a Clinical Trial Ming-Dauh Wang, Dominique A Williams, Elisa V Gomez, and Joyti N Rayamajhi 7. An ROC Approach to Evaluate interim Go/No-Go Decision-making Quality with Application to Futility Stopping in the Clinical Trial Designs Deli Wang, Lu Cui, Lanju Zhang and Bo Yang Part III: Novel Applications and Implementation 8. Recent Advancements in Geovisualization, with a Case Study on Chinese Religions J?rgen Symanzik, Shuming Bao, XiaoTian Dai, Miao Shui and Bing She 9. The Efficiency of Next-Generation Gibbs-Type Samplers: An Illustration Using a Hierarchical Model in Cosmology Xiyun Jiao, David A. van Dyk, Roberto Trotta and Hikmatali Shariff 10. Dynamic Spatial Pattern Recognition in Count Data Xia Wang, Ming-Hui Chen, Rita C. Kuo and Dipak K. Dey 11. Bias-corrected Estimators of Scalar Skew Normal Guoyi Zhang and Rong Liu
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