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Survival Analysis: Techniques for Censored and Truncated Data, Second Edition

John P. Klein and Melvin L. Moeschberger
Publisher: Springer
Copyright: 2003
ISBN-13: 978-0-387-95399-1
Pages: 536; hardcover
Price: $79.50

Comment from the Stata technical group

This text is an essential reference for any researcher using techniques of survival analysis. Ideal for self-study or for a two-term graduate sequence in survival analysis, this book maintains a technical level suited for both the medical researcher and the professional statistician. Most impressive are the number and scope of real-data examples presented in the first chapter and used throughout the text.

Covered topics include basic terminology (e.g., hazards, censoring, mean residual life), nonparametric estimation, life tables, hazard estimation, nonparametric tests, Cox regression (including time-varying covariates and stratification), the additive hazards model, Cox regression diagnostics, parametric regression models, and multivariate analysis, including frailty models.

Table of contents

1 Examples of Survival Data
1.1 Introduction
1.2 Remission Duration from a Clinical Trial for Acute Leukemia
1.3 Bone Marrow Transplantation for Leukemia
1.4 Times to Infection of Kidney Dialysis Patients
1.5 Times to Death for a Breast-Cancer Trial
1.6 Times to Infection for Burn Patients
1.7 Death Times of Kidney Transplant Patients
1.8 Death Times of Male Laryngeal Cancer Patients
1.9 Autologous and Allogeneic Bone Barrow Transplants
1.10 Bone Marrow Transplants for Hodgkin's and Non-Hodgkin's Lymphoma
1.11 Times to Death for Patients with Cancer of the Tongue
1.12 Times to Reinfection for Patients with Sexually Transmitted Diseases
1.13 Time to Hospitalized Pneumonia in Young Children
1.14 Times to Weaning of Breast-Fed Newborns
1.15 Death Times of Psychiatric Patients
1.16 Death Times of Elderly Residents of a Retirement Community
1.17 Time to First Use of Marijuana
1.18 Time to Cosmetic Deterioration of Breast Cancer Patients
1.19 Time to AIDS
2 Basic Quantities and Models
2.1 Introduction
2.2 The Survival Function
2.3 The Hazard Function
2.4 The Mean Residual Life Function and Median Life
2.5 Common Parametric Models for Survival Data
2.6 Regression Models for Survival Data
2.7 Models for Competing Risks
2.8 Exercises
3 Censoring and Truncation
3.1 Introduction
3.2 Right Censoring
3.3 Left or Interval Censoring
3.4 Truncation
3.5 Likelihood Construction for Censored and Truncated Data
3.6 Counting Processes
3.7 Exercises
4 Nonparametric Estimation of Basic Quantities for Right-Censored and Left-Truncated Data
4.1 Introduction
4.2 Estimators of the Survival and Cumulative Hazard Functions for Right-Censored Data
4.3 Pointwise Confidence Intervals for the Survival Function
4.4 Confidence Bands for the Survival Function
4.5 Point and Interval Estimates of the Mean and Median Survival Time
4.6 Estimators of the Survival Function for Left-Truncated and Right-Censored Data
4.7 Summary Curves for Competing Risks
4.8 Exercises
5 Estimation of Basic Quantities for Other Sampling Schemes
5.1 Introduction
5.2 Estimating the Survival Function for Left, Double, and Interval Censoring
5.3 Estimation of the Survival Function for Right-Truncated Data
5.4 Estimation of Survival in the Cohort Life Table
5.5 Exercises
6 Topics in Univariate Estimation
6.1 Introduction
6.2 Estimating the Hazard Function
6.3 Estimation of Excess Mortality
6.4 Bayesian Nonparametric Methods
6.5 Exercises
7 Hypothesis Testing
7.1 Introduction
7.2 One-Sample Tests
7.3 Tests for Two or more Samples
7.4 Tests for Trend
7.5 Stratified Tests
7.6 Renyi Type Tests
7.7 Other Two-Sample Tests
7.8 Test Based on Differences in Outcome at a Fixed Point in Time
7.9 Exercises
8 Semiparametric Proportional Hazards Regression with Fixed Covariates
8.1 Introduction
8.2 Coding Covariates
8.3 Partial Likelihoods for Distinct-Event Time Data
8.4 Partial Likelihoods When Ties Are Present
8.5 Local Tests
8.6 Discretizing a Continuous Covariate
8.7 Model Building Using the Proportional Hazards Model
8.8 Estimation of the Survival Function
8.9 Exercises
9 Refinements of the Semiparametric Proportional Hazards Model
9.1 Introduction
9.2 Time-Dependent Covariates
9.3 Stratified Proportional Hazards Models
9.4 Left Truncation
9.5 Synthesis of Time-varying Effects (Multistate Modeling)
9.6 Exercises
10 Additive Hazards Regression Models
10.1 Introduction
10.2 Aalen's Nonparametric, Additive Hazard Mode
l 10.3 Lin and Ying's Additive Hazards Model
10.4 Exercises
11 Regression Diagnostics
11.1 Introduction
11.2 Cox–Snell Residuals for Assessing the Fit of a Cox Model
11.3 Determining the Functional Form of a Covariate: Martingale Residuals
11.4 Graphical Checks of the Proportional Hazards Assumption
11.5 Deviance Residuals
11.6 Checking the Influence of Individual Observations
11.7 Exercises
12 Inference for Parametric Regression Models
12.1 Introduction
12.2 Weibull Distribution
12.3 Log Logistic Distribution
12.4 Other Parametric Models
12.5 Diagnostic Methods for Parametric Models
12.6 Exercises
13 Multivariate Survival Analysis
13.1 Introduction
13.2 Score Test for Association
13.3 Estimation for the Gamma Frailty Model
13.4 Marginal Model for Multivariate Survival
13.5 Exercises
Appendix A Numerical Techniques for Maximization
A.1 Univariate Methods
A.2 Multivariate Methods
Appendix B Large-Sample Tests Based on Likelihood Theory
Appendix C Statistical Tables
C.1 Standard Normal Survival Function P[ Z ≥ z ]
C.2 Upper Percentiles of a Chi-Square Distribution
C.3a Confidence Coefficients c10(aL,aU) for 90% EP Confidence Bands
C.3b Confidence Coefficients c05(aL,aU) for 95% EP Confidence Bands
C.3c Confidence Coefficients c01(aL,aU) for 99% EP Confidence Bands
C.4a Confidence Coefficients k10(aL,aU) for 90% Hall-Wellner Confidence Bands
C.4b Confidence Coefficients k05(aL,aU) for 95% Hall-Wellner Confidence Bands
C.4c Confidence Coefficients k01(aL,aU) for 99% Hall-Wellner Confidence Bands
C.5 Survival Function of the Supremum of the Absolute Value of a Standard Brownian Motion Process over the Range 0 to 1
C.6 Survival Function of W = ∫0 [ B(t) ]2dt, where B(t) is a Standard Brownian Motion
C.7 Upper Percentiles of R = ∫0k | Bo(u) |du, where Bo(u) is a Brownian Bridge
Appendix D Data on 137 Bone Marrow Transplant Patients
Appendix E Selected Solutions to Exercises
Author Index
Subject Index
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