New Developments in Statistical Modeling, Inference and Application

1. Front Matter

   Pages i-xiv

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2. Theoretical Development in Statistical Modeling

   1. Front Matter

      Pages 1-1

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   2. Dual Model Misspecification in Generalized Linear Models with Error in Variables

      • Xianzheng Huang

      Pages 3-35

   3. Joint Analysis of Longitudinal Data and Informative Observation Times with Time-Dependent Random Effects

      • Yang Li, Xin He, Haiying Wang, Jianguo Sun

      Pages 37-51

   4. A Markov Switching Model with Stochastic Regimes with Application to Business Cycle Analysis

      • Haipeng Xing, Ning Sun, Ying Chen

      Pages 53-76

   5. Direction Estimation in a General Regression Model with Discrete Predictors

      • Yuexiao Dong, Zhou Yu

      Pages 77-88

3. New Developments in Trial Design

   1. Front Matter

      Pages 89-89

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   2. Futility Boundary Design Based on Probability of Clinical Success Under New Drug Development Paradigm

      • Yijie Zhou, Ruji Yao, Bo Yang, Ramachandran Suresh

      Pages 91-105

   3. 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, Jyoti N. Rayamajhi

      Pages 107-119

   4. 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, Bo Yang

      Pages 121-147

4. Novel Applications and Implementation

   1. Front Matter

      Pages 149-149

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   2. Recent Advancements in Geovisualization, with a Case Study on Chinese Religions

      • Jürgen Symanzik, Shuming Bao, XiaoTian Dai, Miao Shui, Bing She

      Pages 151-166

   3. The Efficiency of Next-Generation Gibbs-Type Samplers: An Illustration Using a Hierarchical Model in Cosmology

      • Xiyun Jiao, David A. van Dyk, Roberto Trotta, Hikmatali Shariff

      Pages 167-184

   4. Dynamic Spatial Pattern Recognition in Count Data

      • Xia Wang, Ming-Hui Chen, Rita C. Kuo, Dipak K. Dey

      Pages 185-202

   5. Bias-corrected Estimators of Scalar Skew Normal

      • Guoyi Zhang, Rong Liu

      Pages 203-214

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.

• Bayesian
• clinical trials
• clinical trial design
• diagnostic medicine
• high-dimensional data mining
• modeling
• data analysis
• personalized medicine
• innovative clinical design
• model misspecification
• clinical trial analysis
• futility design
• Bayesian statistics
• applied statistics
• data mining

• Mailman School of Public Health Department of Biostatistics, Columbia University, New York, USA

  Zhezhen Jin

• Division of Biostatistics, NYU School of Medicine, New York, USA

  Mengling Liu

• Biostatistics Celgene Corporation, Summit, USA

  Xiaolong Luo

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. 

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