"Handbook of Statistics in Clinical Oncology" ed. by John Crowley (Repost)

Compendium of statistical approaches to the problems facing researchers. Focuses on cancer clinical trials, with a few contributions applying to observational studies. For statisticians working in cancer research and also oncologists.

This book compiles state-of-the-art statistical approaches to solving problems in clinical oncology.
Examines trial design treatment based on toxicity and survival! Featuring over 1000 references, more than 40 world-renowned contributors, and 300 equations, tables, and drawings, the Handbook of Statistics in Clinical Oncology provides a comprehensive discussion of sample size considers analytical problems generated by controlling treatment costs and maintaining quality of life demonstrates the breadth and depth of current activity in the field of survival analysis sets the limits on what can and cannot be concluded from single and multiple clinical trials and more! The best single source for up-to-date graphical, tree-based, and other statistical methods, the Handbook of Statistics in Clinical Oncology is fascinating reading for oncologists, cancer researchers, biostatisticians, applied statisticians, and medical and graduate students in these disciplines.

Contents
Preface
Contributors
PHASE I TRIALS
1. Overview of Phase I Trials - Lutz Edler
2. Dose-Finding Designs Using Continual Reassessment Method - John O’Quigley
3. Choosing a Phase I Design - Barry E. Storer
PHASE II TRIALS
4. Overview of Phase II Clinical Trials - Stephanie Green
5. Designs Based on Toxicity and Response - Gina R. Petroni and Mark R. Conaway
6. Phase II Selection Designs - P. Y. Liu
PHASE III TRIALS
7. Power and Sample Size for Phase III Clinical Trials of Survival - Jonathan J. Shuster
8. Multiple Treatment Trials - Stephen L. George
9. Factorial Designs with Time-to-Event End Points - Stephanie Green
10. Therapeutic Equivalence Trials - Richard Simon
11. Early Stopping of Cancer Clinical Trials - James J. Dignam, John Bryant, and H. Samuel Wieand
12. Use of the Triangular Test in Sequential Clinical Trials - John Whitehead
COMPLEMENTARY OUTCOMES
13. Design and Analysis Considerations for Complementary Outcomes - Bernard F. Cole
14. Health-Related Quality-of-Life Outcomes - Benny C. Zee and David Osoba
15. Statistical Analysis of Quality of Life - Andrea B. Troxel and Carol McMillen Moinpour
16. Economic Analysis of Cancer Clinical Trials - Gary H. Lyman
PROGNOSTIC FACTORS AND EXPLORATORY ANALYSIS
17. Prognostic Factor Studies - Martin Schumacher, Norbert Hollander, Guido Schwarzer, and Willi Sauerbrei
18. Statistical Methods to Identify Prognostic Factors - Kurt Ulm, Hjalmar Nekarda, Pia Gerein, and Ursula Berger
19. Explained Variation in Proportional Hazards Regression - John O’Quigley and Ronghui Xu
20. Graphical Methods for Evaluating Covariate Effects in the Cox Model - Peter F. Thall and Elihu H. Estey
21. Graphical Approaches to Exploring the Effects of Prognostic Factors on Survival - Peter D. Sasieni and Angela Winnett
22. Tree-Based Methods for Prognostic Stratification - Michael LeBlanc
INTERPRETING CLINICAL TRIALS
23. Problems in Interpreting Clinical Trials - Lilllian L. Siu and Ian F. Tannock
24. Commonly Misused Approaches in the Analysis of Cancer Clinical Trials - James R. Anderson
25. Dose-Intensity Analysis - Joseph L. Pater
26. Why Kaplan-Meier Fails and Cumulative Incidence Succeeds When Estimating Failure Probabilities in the Presence of Competing Risks - Ted A. Gooley, Wendy Leisenring, John Crowley, and Barry E. Storer
27. Meta-Analysis - Luc Duchateau and Richard Sylvester
Index