New Developments in Statistical Modeling, Inference and Application

Selected Papers from the 2014 ICSA/KISS Joint Applied Statistics Symposium in Portland, OR
1. Auflage 2016
ISBN: 978-3-319-42570-2
Verlag: Springer International Publishing

Buch, Englisch, 214 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 4675 g

Reihe: ICSA Book Series in Statistics

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.

Zielgruppe

Research

Autoren/Hrsg.

Jin, Zhezhen

Luo, Xiaolong

Liu, Mengling

Fachgebiete

• Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik

Inhaltsverzeichnis

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

Jürgen 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

Über Autor(innen)

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.