Survival Analysis Using the Sas System: A Practical Guide,9781555442798

Survival Analysis Using the Sas System: A Practical Guide

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ISBN13: 9781555442798
ISBN10: 155544279X
Format: Paperback
Pub. Date: 1997-03-01
Publisher(s): SAS INSTITUTE, INCORPORATED
List Price: $45.33

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Summary

Biomedical and social science researchers who want to analyze survival data with SAS will find just what they need with this easy-to-read and comprehensive guide. Written for the reader with a modest statistical background and minimal knowledge of SAS software, this book teaches many aspects of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical book ensuring that even the uninitiated becomes a sophisticated user of survival analysis. The man topics presented include censoring, survival curve, Kaplan-Meier estimation, accelerated failure time models, Cox regression models, and discrete-time analysis. Also included are topics not usually covered such as time-dependent covariates, competing risks, and repeated events.

Author Biography

Paul D. Allison is Professor of Sociology at the University of Pennsylvania

Table of Contents

Acknowledgments iii
Introduction
1(8)
What is Survival Analysis?
1(1)
What is Survival Data?
2(2)
Why Use Survival Analysis?
4(1)
Approaches to Survival Analysis
5(1)
What You Need to Know
6(1)
Computing Notes
7(2)
Basic Concepts of Survival Analysis
9(20)
Introduction
9(1)
Censoring
9(5)
Describing Survival Distributions
14(3)
Interpretations of the Hazard Function
17(2)
Some Simple Hazard Models
19(3)
The Origin of Time
22(3)
Data Structure
25(4)
Estimating and Comparing Survival Curves with Proc Lifetest
29(32)
Introduction
29(1)
The Kaplan-Meir Method
30(6)
Testing for Differences in Survivor Functions
36(5)
The Life-Table Method
41(8)
Life Tables from Grouped Data
49(3)
Testing for the Effects of Covariates
52(4)
Log Survival and Smoothed Hazard Plots
56(3)
Conclusion
59(2)
Estimating Parametric Regression Models with Proc Lifereg
61(50)
Introduction
61(1)
The Accelerated Failure Time Model
62(4)
Alternative Distributions
66(12)
Categorical Variables and the CLASS Statement
78(1)
Maximum Likelihood Estimation
79(6)
Hypothesis Tests
85(3)
Goodness-of-Fit Tests with the Likelihood-Ratio Statistic
88(3)
Graphical Methods for Evaluating Model Fit
91(6)
Left Censoring and Interval Censoring
97(4)
Generating Predictions and Hazard Functions
101(3)
The Piecewise Exponential Model
104(5)
Conclusion
109(2)
Estimating Cox Regression Models with Proc Phreg
111(74)
Introduction
111(2)
The Proportional Hazards Model
113(1)
Partial Likelihood
114(13)
Tied Data
127(11)
Time-Dependent Covariates
138(16)
Cox Models with Nonproportional Hazards
154(1)
Interactions with Time as Time-Dependent Covariates
155(3)
Nonproportionality via Stratification
158(3)
Left Truncation and Late Entry into the Risk Set
161(4)
Estimating Survivor Functions
165(8)
Residuals and Influence Statistics
173(8)
Testing Linear Hypotheses with the TEST Statement
181(2)
Conclusion
183(2)
Competing Risks
185(26)
Introduction
185(1)
Type-Specific Hazards
186(3)
Time in Power for Leaders of Countries: Example
189(1)
Estimates and Tests without Covariates
190(5)
Covariate Effects via Cox Models
195(5)
Accelerated Failure Time Models
200(6)
An Alternative Approach to Multiple Event Types
206(2)
Conclusion
208(3)
Analysis of Tied or Discrete Data with the LOGISTIC, PROBIT, and GENMOD Procedures
211(22)
Introduction
211(1)
The Logit Model for Discrete Time
212(4)
The Complementary Log-Log Model for Continuous-Time Processes
216(3)
Data with Time-Dependent Covariates
219(4)
Issues and Extensions
223(8)
Conclusion
231(2)
Heterogeneity, Repeated Events, and Other Topics
233(20)
Introduction
233(1)
Unobserved Heterogeneity
233(3)
Repeated Events
236(11)
Generalized R2
247(2)
Sensitivity Analysis for Informative Censoring
249(4)
A Guide for the Perplexed
253(6)
How to Choose a Method
253(3)
Conclusion
256(3)
Appendix 1 Macro Programs 259(10)
Introduction
259(1)
The SMOOTH Macro
259(2)
The LIFEHAZ Macro
261(2)
The PREDICT Macro
263(1)
The WLW Macro
264(5)
Appendix 2 Data Sets 269(8)
Introduction
269(1)
The MYEL Data Set: Myelomatosis Patients
269(1)
The RECID Data Set: Arrest Times for Released Prisoners
270(1)
The STAN Data Set: Stanford Heart Transplant Patients
271(1)
The BREAST Data Set: Survival Data for Breast Cancer Patients
272(1)
The JOBDUR Data Set: Durations of Jobs
272(1)
The ALCO Data Set: Survival of Cirrhosis Patients
272(1)
The LEADERS Data Set: Time in Power for Leaders of Countries
273(1)
The RANK Data Set: Promotions in Rank for Biochemists
274(1)
The JOBMULT Data Set: Repeated Job Changes
275(2)
References 277(6)
Index 283

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