Preface xi
1. Introduction to Regression Modeling of Survival Data 1
2. Descriptive Methods for Survival Data 16
3. Regression Models for Survival Data 67
4. Interpretation of a Fitted Proportional Hazards Regression Model 92
5. Model Development 132
6. Assessment of Model Adequacy 169
7. Extensions of the Proportional Hazards Model 207
8. Parametric Regression Models 244
9. Other Models and Topics 286
Appendix 1: The Delta Method 355
Appendix 2: An Introduction to the Counting Process Approach to Survival Analysis 359
Appendix 3: Percentiles for Computation of the Hall and Wellner Confidence Band 364
References 365
Index 383
David W. Hosmer, PhD, is Professor Emeritus of Biostatistics in the School of Public Health and Heatlth Sciences at the University of Massachusetts Amherst. Dr. Hosmer is the coauthor of Applied Logistic Regression, published by Wiley.
Stanley Lemeshow, PhD, is Professor and Dean of the College of Public Health at The Ohio State University. Dr. Lemeshow has over thirty-five years of academic experience in the areas of regression, categorical data methods, and sampling methods. He is the coauthor of Sampling of Population: Methods and Application and Applied Logistic Regression, both published by Wiley.
Susanne May, PhD, is Assistant Professor of Biostatistics at the University of California, San Diego. Dr. May has over twelve years of experience in providing statistical support for health-related research projects.
“This is a great book for anyone analyzing time-to-event data. Researchers interested in the underlying theory will have to go elsewhere..” (Stat Papers, 1 December 2012) "It is well suited for teaching a graduate-level course in medical statistics, and the data sets used in the book are available online." (Biometrical Journal, August 2009) "This is a superb resource - a practical guide with up-to-date applications. The authors are excellent teachers of the mathematics and application of survival data regression modeling." (Doodys, August 2009) "The extensive and detailed coverage of the process of survival model fitting, as well as the applied exercises, make this textbook an excellent choice for an applied survival analysis course." (Journal of Biopharmaceutical Statistics, Volume 18, Issue 6, 2008)
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