Survival Analysis Using the SAS System: A Practical Guide
CONTENTS
ACKNOWLEDGMENTS iii
Chapter 1 Introduction
- p. 1 What is Survival Analysis?
- p. 2 What is Survival Data?
- p. 4 Why Use Survival Analysis?
- p. 5 Approaches to Survival Analysis
- p. 6 What You Need to Know
- p. 7 Computing Notes
Chapter 2 Basic Concepts of Survival Analysis
- p. 9 Introduction
- p. 9 Censoring
- p. 14 Describing Survival Distributions
- p. 17 Interpretations of the Hazard Function
- p. 19 Some Simple Hazard Models
- p. 22 The Origin of Time
- p. 25 Data Structure
Chapter 3 Estimating and Comparing Survival Curves with
- PROC LIFETEST
- p. 29 Introduction
- p. 30 The Kaplan-Meir Method
- p. 36 Testing for Differences in Survivor Functions
- p. 41 The Life-Table Method
- p. 49 Life Tables from Grouped Data
- p. 52 Testing for the Effects of Covariates
- p. 56 Log Survival and Smoothed Hazard Plots
- p. 59 Conclusion
Chapter 4 Estimating Parametric Regression Models with
- PROC LIFEREG
- p. 61 Introduction
- p. 62 The Accelerated Failure Time Model
- p. 66 Alternative Distributions
- p. 78 Categorical Variables and the CLASS Statement
- p. 79 Maximum Likelihood Estimation
- p. 85 Hypothesis Tests
- p. 88 Goodness-of-Fit Tests with the Likelihood-Ratio Statistic
- p. 91 Graphical Methods for Evaluating Model Fit
- p. 97 Left Censoring and Interval Censoring
- p.101 Generating Predictions and Hazard Functions
- p.104 The Piecewise Exponential Model
- p.109 Conclusion
Chapter 5 Estimating Cox Regression Models with
- PROC PHREG
- p.111 Introduction
- p.113 The Proportional Hazards Model
- p.114 Partial Likelihood
- p.127 Tied Data
- p.138 Time-Dependent Covariates
- p.154 Cox Models with Nonproportional Hazards
- p.155 Interactions with Time as Time-Dependent Covariates
- p.158 Nonproportionality via Stratification
- p.161 Left Truncation and Late Entry into the Risk Set
- p.165 Estimating Survivor Functions
- p.173 Residuals and Influence Statistics
- p.181 Testing Linear Hypotheses with the TEST Statement
- p.183 Conclusion
Chapter 6 Competing Risks
- p.185 Introduction
- p.186 Type-Specific Hazards
- p.189 Time in Power for Leaders of Countries: Example
- p.190 Estimates and Tests without Covariates
- p.195 Covariate Effects via Cox Models
- p.200 Accelerated Failure Time Models
- p.206 An Alternative Approach to Multiple Event Types
- p.208 Conclusion
Chapter 7 Analysis of Tied or Discrete Data with the
- LOGISTIC, PROBIT, and GENMOD Procedures
- p.211 Introduction
- p.212 The Logit Model for Discrete Time
- p.216 The Complementary Log-Log Model for Continuous-Time Processes
- p.219 Data with Time-Dependent Covariates
- p.223 Issues and Extensions
- p.231 Conclusion
Chapter 8 Heterogeneity, Repeated Events, and
- Other Topics
- p.233 Introduction
- p.233 Unobserved Heterogeneity
- p.236 Repeated Events
- p.247 Generalized R
- p.249 Sensitivity Analysis for Informative Censoring
Chapter 9 A Guide for the Perplexed
- p.253 How to Choose a Method
- p.256 Conclusion
Appendix 1 Macro Programs
p.259 Introduction
p.259 The SMOOTH Macro
p.261 The LIFEHAZ Macro
p.263 The PREDICT Macro
p.264 The WLW Macro
Appendix 2 Data Sets
p.269 Introduction
p.269 The MYEL Data Set: Myelomatosis Patients
p.270 The RECID Data Set: Arrest Times for Released Prisoners
p.271 The STAN Data Set: Stanford Heart Transplant Patients
p.272 The BREAST Data Set: Survival Data for Breast Cancer Patients
p.272 The JOBDUR Data Set: Durations of Jobs
p.272 The ALCO Data Set: Survival of Cirrhosis Patients
p.273 The LEADERS Data Set: Time in Power for Leaders of Countries
p.274 The RANK Data Set: Promotions in Rank for Biochemists
p.275 The JOBMULT Data Set: Repeated Job Changes
References
Index