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The papers in this volume represent a broad, applied swath of advanced contributions to the 2015 ICSA/Graybill Applied Statistics Symposium of the International Chinese Statistical Association, held at Colorado State University in Fort Collins. The contributions cover topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. Each papers 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.
Focuses on statistical applications from clinical trials, biomarker analysis, and personalized medicine to applications in finance and business analytics A unique selection of papers from broad and multi-disciplinary critical hot topics - from academic, government, and industry perspectives - to appeal to a wide variety of applied research interests All papers feature original, peer-reviewed content Includes supplementary material: sn.pub/extras
Auteur
Jianchang Lin, Ph.D., is Principal Statistician at Takeda Pharmaceuticals, with extensive experience in oncology drug clinical development, including leading successful NDA/MAA submissions and worldwide drug approvals. Dr. Lin's research interests include Bayesian methodologies, survival analysis and Bayesian adaptive designs, and their application in clinical trials.
Bushi Wang, Ph.D., is a biostatistician at Boehringer Ingelheim Pharmaceuticals, Inc. He researches clinical trials across different therapeutic areas and different phases, largely focusing on late stage oncology and cardiovascular trials, supporting approval. He is co-founder of the Multiple Comparison Procedures Society, a .U.S organization supporting the international MCP conferences.
Xiaowen Hu, Ph.D., is Assistant Professor in the Department of Statistics, Colorado State University. Her research interests include spatial analysis, time series analysis, Bayesian analysis, and statistical analysis in business and empirical finance.
Kun Chen, Ph.D., is Assistant Professor in the Department of Statistics, University of Connecticut. His research interests include multivariate analysis, dimension reduction, robust statistics, statistical computing and their broad applications in ecology, genetics, public health, and other areas of applied statistics.
Ray Liu, Ph.D., is Head of the Statistical Innovation and Consultation Center at Takeda Pharmaceuticals, Inc. His research interests include design and analysis of omics studies, integrated analysis, and text mining.
Contenu
[cutting to roughly 30 papers]
Generalized Confidence Interval Approach for A Statistical Decision Framework Applicable to Multipopulation Tailoring Trials
Multi-Regional Clinical Trials Where we have been and where we are going
Composite endpoints: Some common misconceptions
DIA Adaptive Design Scientific Working Group Best Practices Team: Objectives and Case Studies
Methods for Flexible Sample-Size Design in Clinical Trials
Statistical Challenges in Testing Multiple Endpoints in Complex Trial Designs
Generalized Holm's procedure for multiple testing problem
Identification of Biomarker Signatures Using Adaptive Elastic Net
Design and Analysis of Multiregional Clinical Trials in Evaluation of Medical Devices: A Two-component Bayesian Approach for Targeted Regulatory Decision Making
Evaluation of strategies for designing Phase 2 dose finding studies
Bayesian Hierarchical Monotone Regression I-splines for Dose-Response Assessment and Drug-Drug Interaction Analysis
Continuous Safety Signal Monitoring with Blinded Data
Bayesian integration of in vitro biomarker data to in vivo safety assessment
Bayesian Path Specific Frailty Models for Multi-state Survival Data with Applications
Sample Size Allocation in a Dose-Ranging Trial Combined with PoC 18. A Bayesian Approach For Subgroup Analysis
Design Considerations in Dose Finding Studies
Identifying Predictive Biomarkers in A Dose-Response Study
A nationwide cohort study of Influenza vaccine on stroke prevention in the chronic kidney disease population
Multivariate Spatial Modeling on Spheres
Statistical Method for Change-set Analysis
Statistical Issues in Health Related Quality of Life research
Analysis of clustered longitudinal/functional data
Variable Selection Methods for Functional Regression Models
Promoting Similarity of Sparsity Structures in Integrative Analysis
Bayesian Nonlinear Model Selection for Gene Regulatory Networks
Innovated Interaction Screening for High-Dimensional Nonlinear Classification
Spatial Bayesian Hierarchical Model for small area estimation of categorical data
Evaluate the Most Accurate Animal Model With Application to Pediatric Medulloblastoma
Analysis Optimization for Biomarker and Subgroup Identification
Statistical Methods for Analytical Comparability36. Design and Statistical Analysis of Multidrug Combinations in Preclinical Studies and Clinical Trials
Correcting Ascertainment Bias in Biomarker Identification
Subgroup-Based Adaptive (SUBA) Designs for Multi-Arm Biomarker Trials
ROC-based meta analysis with individual level information
Optimal Marker-Adaptive Designs for Targeted Therapy Based on Imperfectly Measured Biomarkers
Statistical considerations for evaluating prognostic imaging biomarkers
Stacking survival models.- Estimation of Discrete Survival Function through the Modeling of Diagnostic Accuracy for Mismeasured Outcome Data
A Bivariate Copula Random-Effects Model for Length of Stay and Cost
Non-inferiority tests for prognostic models
Economic Movement and Mental Health: A Population-based Study
Hypothesis Test of Mediation Effect in Causal Mediation Model with High-dimensional Mediators