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A Guide for the Perplexed
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A Guide for the Perplexed
by Paul D. Allison
Survival Analysis Using SAS®: A Practical Guide
Copyright
Acknowledgments
Introduction
What Is Survival Analysis?
What Is Survival Data?
Why Use Survival Analysis?
Approaches to Survival Analysis
What You Need to Know
Computing Notes
Basic Concepts of Survival Analysis
Introduction
Censoring
Describing Survival Distributions
Interpretations of the Hazard Function
Some Simple Hazard Models
The Origin of Time
Data Structure
Estimating and Comparing Survival Curves with PROC LIFETEST
Introduction
The Kaplan-Meier Method
Testing for Differences in Survivor Functions
The Life-Table Method
Life Tables from Grouped Data
Testing for Effects of Covariates
Log Survival and Smoothed Hazard Plots
Conclusion
Estimating Parametric Regression Models with PROC LIFEREG
Introduction
The Accelerated Failure Time Model
Alternative Distributions
Categorical Variables and the CLASS Statement
Maximum Likelihood Estimation
Hypothesis Tests
Goodness-of-Fit Tests with the Likelihood-Ratio Statistic
Graphical Methods for Evaluating Model Fit
Left Censoring and Interval Censoring
Generating Predictions and Hazard Functions
The Piecewise Exponential Model
Conclusion
Estimating Cox Regression Models with PROC PHREG
Introduction
The Proportional Hazards Model
Partial Likelihood
Tied Data
Time-Dependent Covariates
Cox Models with Nonproportional Hazards
Left Truncation and Late Entry into the Risk Set
Estimating Survivor Functions
Residuals and Influence Statistics
Testing Linear Hypotheses with the TEST Statement
Conclusion
Competing Risks
Introduction
Type-Specific Hazards
Time in Power for Leaders of Countries: Example
Estimates and Tests Without Covariates
Covariate Effects Via Cox Models
Accelerated Failure Time Models
An Alternative Approach to Multiple Event Types
Conclusion
Analysis of Tied or Discrete Data with the LOGISTIC, PROBIT, and GENMOD Procedures
Introduction
The Logit Model for Discrete Time
The Complementary Log-Log Model for Continuous-Time Processes
Data with Time-Dependent Covariates
Issues and Extensions
Conclusion
Heterogeneity, Repeated Events, and Other Topics
Introduction
Unobserved Heterogeneity
Repeated Events
Generalized R2
Sensitivity Analysis for Informative Censoring
A Guide for the Perplexed
How to Choose a Method
Conclusion
Macro Programs
Introduction
The SMOOTH Macro
The LIFEHAZ Macro
The WLW Macro
Data Sets
Introduction
The MYEL Data Set: Myelomatosis Patients
The RECID Data Set: Arrest Times for Released Prisoners
The STAN Data Set: Stanford Heart Transplant Patients
The BREAST Data Set: Survival Data for Breast Cancer Patients
The JOBDUR Data Set: Durations of Jobs
The ALCO Data Set: Survival of Cirrhosis Patients
The LEADERS Data Set: Time in Power for Leaders of Countries
The RANK Data Set: Promotions in Rank for Biochemists
The JOBMULT Data Set: Repeated Job Changes
References
Books Available from SAS Press
JMP® Books
Index
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Sensitivity Analysis for Informative Censoring
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How to Choose a Method
Chapter 9. A Guide for the Perplexed
p.
253
How to Choose a Method
p.
256
Conclusion
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