Survival Analysis

1. Front Matter

   Pages i-xiv

   PDF

2. Examples of Survival Data

   • John P. Klein, Melvin L. Moeschberger

   Pages 1-20

3. Basic Quantities and Models

   • John P. Klein, Melvin L. Moeschberger

   Pages 21-53

4. Censoring and Truncation

   • John P. Klein, Melvin L. Moeschberger

   Pages 55-82

5. Nonparametric Estimation of Basic Quantities for Right-Censored and Left-Truncated Data

   • John P. Klein, Melvin L. Moeschberger

   Pages 83-124

6. Estimation of Basic Quantities for Other Sampling Schemes

   • John P. Klein, Melvin L. Moeschberger

   Pages 125-150

7. Topics in Univariate Estimation

   • John P. Klein, Melvin L. Moeschberger

   Pages 151-186

8. Hypothesis Testing

   • John P. Klein, Melvin L. Moeschberger

   Pages 187-227

9. Semiparametric Proportional Hazards Regression with Fixed Covariates

   • John P. Klein, Melvin L. Moeschberger

   Pages 229-268

10. Refinements of the Semiparametric Proportional Hazards Model

    • John P. Klein, Melvin L. Moeschberger

    Pages 269-303

11. Additive Hazards Regression Models

    • John P. Klein, Melvin L. Moeschberger

    Pages 305-326

12. Regression Diagnostics

    • John P. Klein, Melvin L. Moeschberger

    Pages 327-371

13. Inference for Parametric Regression Models

    • John P. Klein, Melvin L. Moeschberger

    Pages 373-403

14. Multivariate Survival Analysis

    • John P. Klein, Melvin L. Moeschberger

    Pages 405-421

15. Back Matter

    Pages 423-502

    PDF

Applied statisticians in many fields must frequently analyze time to event data. While the statistical tools presented in this book are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography, the focus here is on applications of the techniques to biology and medicine. The analysis of survival experiments is complicated by issues of censoring, where an individual's life length is known to occur only in a certain period of time, and by truncation, where individuals enter the study only if they survive a sufficient length of time or individuals are included in the study only if the event has occurred by a given date. The use of counting process methodology has allowed for substantial advances in the statistical theory to account for censoring and truncation in survival experiments. This book makes these complex methods more accessible to applied researchers without an advanced mathematical background. The authors present the essence of these techniques, as well as classical techniques not based on counting processes, and apply them to data. Practical suggestions for implementing the various methods are set off in a series of Practical Notes at the end of each section. Technical details of the derivation of the techniques are sketched in a series of Technical Notes. This book will be useful for investigators who need to analyze censored or truncated life time data, and as a textbook for a graduate course in survival analysis. The prerequisite is a standard course in statistical methodology. "This book...offers an excellent course in survival analysis for

• Excel
• Maxima
• Percentile
• biology
• cancer
• censoring
• diagnostics
• epidemiology
• health
• medicine
• public health
• statistical method
• statistical theory
• survival analysis
• truncated data

• Division of Biostatistics, Medical College of Wisconsin, Milwaukee, USA

  John P. Klein

• School of Public Health, Division of Epidemiology and Biometrics, The Ohio State University Medical Center, Columbus, USA

  Melvin L. Moeschberger

Policies and ethics