Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics
Selected Papers from the 2015 ICSA/Graybill Applied Statistics Symposium, Colorado State University, Fort Collins
(Sprache: Englisch)
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...
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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.
Inhaltsverzeichnis zu „Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics “
[cutting to roughly 30 papers]1. Generalized Confidence Interval Approach for A Statistical Decision Framework Applicable to Multipopulation Tailoring Trials
2. Multi-Regional Clinical Trials - Where we have been and where we are going
3. Composite endpoints: Some common misconceptions
4. DIA Adaptive Design Scientific Working Group Best Practices Team: Objectives and Case Studies
5. Methods for Flexible Sample-Size Design in Clinical Trials
6. Statistical Challenges in Testing Multiple Endpoints in Complex Trial Designs
7. Generalized Holm's procedure for multiple testing problem
8. Assessing Benefit and Consistency of Treatment Effect under a Discrete Random Effects Model in Multiregional Clinical Trials9. Multiplicity Adjustment in Vaccine Efficacy Trial with Adaptive Population-Enrichment Design
10. Identification of Biomarker Signatures Using Adaptive Elastic Net
11. Design and Analysis of Multiregional Clinical Trials in Evaluation of Medical Devices: A Two-component Bayesian Approach for Targeted Regulatory Decision Making
12. Evaluation of strategies for designing Phase 2 dose finding studies
13. Bayesian Hierarchical Monotone Regression I-splines for Dose-Response Assessment and Drug-Drug Interaction Analysis
14. Continuous Safety Signal Monitoring with Blinded Data
15. Bayesian integration of in vitro biomarker data to in vivo safety assessment
16. Bayesian Path Specific Frailty Models for Multi-state Survival Data with Applications
17. Sample Size Allocation in a Dose-Ranging Trial Combined with PoC
18. A Bayesian Approach For Subgroup Analysis
19. Design Considerations in Dose Finding Studies
20. Identifying Predictive Biomarkers in A Dose-Response Study
21. A nationwide cohort study of Influenza vaccine on stroke prevention in the chronic kidney disease
... mehr
population
22. Multivariate Spatial Modeling on Spheres
23. Statistical Method for Change-set Analysis
24. Statistical Issues in Health Related Quality of Life research
25. Analysis of clustered longitudinal/functional data
26. Variable Selection Methods for Functional Regression Models
27. Promoting Similarity of Sparsity Structures in Integrative Analysis
28. Optimal Estimation for The Functional Cox Model29. Bayesian Spatial Clustering Method and Its Application In Radiology
30. Bayesian Nonlinear Model Selection for Gene Regulatory Networks
31. Innovated Interaction Screening for High-Dimensional Nonlinear Classification
32. Spatial Bayesian Hierarchical Model for small area estimation of categorical data
33. Evaluate the Most Accurate Animal Model With Application to Pediatric Medulloblastoma
34. Analysis Optimization for Biomarker and Subgroup Identification
35. Statistical Methods for Analytical Comparability<
36. Design and Statistical Analysis of Multidrug Combinations in Preclinical Studies and Clinical Trials
37. Composite Kernel Machine Regression Based on Likelihood Ratio Test and its Application on Genomic Studies38. Statistical Applications for Biosimilar Product Development
39. Correcting Ascertainment Bias in Biomarker Identification
40. Subgroup-Based Adaptive (SUBA) Designs for Multi-Arm Biomarker Trials
41. ROC-based meta analysis with individual level information
42. Optimal Marker-Adaptive Designs for Targeted Therapy Based on Imperfectly Measured Biomarkers
43. Statistical considerations for evaluating prognostic imaging biomarkers
44. Stacking survival models.- Estimation of Discrete Survival Function through the Modeling of Diagnostic Accuracy for Mismeasured Outcome Data
45. A Bivariate Copula Random-Effects Model for Length of Stay and Cost
46. Non-inferiority tests for prognostic models
47. Explained Variation in Correlated Survival Data48. Web-based Analytics for Business Decision Making
49. Economic Movement and Mental Health: A Population-based Study
50. Hypothesis Test of Mediation Effect in Causal Mediation Model with High-dimensional Mediators
22. Multivariate Spatial Modeling on Spheres
23. Statistical Method for Change-set Analysis
24. Statistical Issues in Health Related Quality of Life research
25. Analysis of clustered longitudinal/functional data
26. Variable Selection Methods for Functional Regression Models
27. Promoting Similarity of Sparsity Structures in Integrative Analysis
28. Optimal Estimation for The Functional Cox Model29. Bayesian Spatial Clustering Method and Its Application In Radiology
30. Bayesian Nonlinear Model Selection for Gene Regulatory Networks
31. Innovated Interaction Screening for High-Dimensional Nonlinear Classification
32. Spatial Bayesian Hierarchical Model for small area estimation of categorical data
33. Evaluate the Most Accurate Animal Model With Application to Pediatric Medulloblastoma
34. Analysis Optimization for Biomarker and Subgroup Identification
35. Statistical Methods for Analytical Comparability<
36. Design and Statistical Analysis of Multidrug Combinations in Preclinical Studies and Clinical Trials
37. Composite Kernel Machine Regression Based on Likelihood Ratio Test and its Application on Genomic Studies38. Statistical Applications for Biosimilar Product Development
39. Correcting Ascertainment Bias in Biomarker Identification
40. Subgroup-Based Adaptive (SUBA) Designs for Multi-Arm Biomarker Trials
41. ROC-based meta analysis with individual level information
42. Optimal Marker-Adaptive Designs for Targeted Therapy Based on Imperfectly Measured Biomarkers
43. Statistical considerations for evaluating prognostic imaging biomarkers
44. Stacking survival models.- Estimation of Discrete Survival Function through the Modeling of Diagnostic Accuracy for Mismeasured Outcome Data
45. A Bivariate Copula Random-Effects Model for Length of Stay and Cost
46. Non-inferiority tests for prognostic models
47. Explained Variation in Correlated Survival Data48. Web-based Analytics for Business Decision Making
49. Economic Movement and Mental Health: A Population-based Study
50. Hypothesis Test of Mediation Effect in Causal Mediation Model with High-dimensional Mediators
... weniger
Autoren-Porträt
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.
Bibliographische Angaben
- 2018, Softcover reprint of the original 1st ed. 2016, XV, 359 Seiten, 44 farbige Abbildungen, Maße: 15,6 x 23,3 cm, Kartoniert (TB), Englisch
- Herausgegeben: Jianchang Lin, Bushi Wang, Xiaowen Hu, Kun Chen, Ray Liu
- Verlag: Springer, Berlin
- ISBN-10: 3319826107
- ISBN-13: 9783319826103
Sprache:
Englisch
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