Jianrong Wu

Statistical Methods for Survival Trial Design (eBook, PDF)

With Applications to Cancer Clinical Trials Using R

• Format: PDF

Produktbeschreibung

Statistical Methods for Survival Trial Design: With Applications to Cancer Clinical Trials Using R provides a thorough presentation of the principles of designing and monitoring cancer clinical trials in which time-to-event is the primary endpoint. Traditional cancer trial designs with time-to-event endpoints are often limited to the exponential model or proportional hazards model. In practice, however, those model assumptions may not be satisfied for long-term survival trials.

This book is the first to cover comprehensively the many newly developed methodologies for survival trial design, including trial design under the Weibull survival models; extensions of the sample size calculations under the proportional hazard models; and trial design under mixture cure models, complex survival models, Cox regression models, and competing-risk models. A general sequential procedure based on the sequential conditional probability ratio test is also implemented for survival trial monitoring. All methodologies are presented with sufficient detail for interested researchers or graduate students.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 273
• Erscheinungstermin: 14. Juni 2018
• Englisch
• ISBN-13: 9780429892943
• Artikelnr.: 56831879

Autorenporträt

Jianrong (John) Wu is a professor in the Division of Cancer Biostatistics, Department of Biostatistics, Markey Cancer Center, University of Kentucky. He has more than 15 years' experience of designing and conducting cancer clinical trials at St. Jude Children's Research Hospital and has developed several novel statistical methods for designing phase II and phase III survival trials.

Inhaltsangabe

Preface List of Figures List of Tables 1. Introduction to Cancer Clinical
Trials General Aspects of Cancer Clinical Trial Design Study Objectives
Treatment Plan Eligibility Criteria Statistical Considerations Statistical
Aspects of Cancer Survival Trial Design Randomization Stratification
Blinding Sample Size Calculation 2. Survival Analysis Survival Distribution
Exponential Distribution Weibull Distribution Gamma Distribution Gompertz
Distribution Log-Normal Distribution Log-Logistic Distribution Survival
Data Fitting the Parametric Survival Distribution Kaplan-Meier Estimates
Median Survival Time Log-Rank Test Cox Regression Model 3. Counting Process
and Martingale_ Basic Convergence Concepts Counting Process Definition
Martingale Central Limit Theorem Counting Process Formulation of Censored
Survival Data 4. Survival Trial Design Under the Parametric Model
Introduction Weibull Model Test Statistic Distribution of the MLE test
Sample Size Formula Sample Size Calculation Accrual Duration Calculation
Example and R code 5. Survival Trial Design Under the Proportional Hazards
Model Introduction Proportional Hazards Model Asymptotic Distribution of
the Log-rank Test Schoenfeld Formula Rubinstein Formula Freedman Formula
Comparison Sample Size Calculation Under Various Models Example Optimal
Properties of the Log-Rank Test_ Optimal Sample Size Allocation Optimal
Power Precise Formula <