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Survival analysis using the SAS system : a practical guide / Paul D. Allison.
LIBRA QA276.4 .A394 1995
Available from offsite location
- Format:
- Book
- Author/Creator:
- Allison, Paul David.
- Language:
- English
- Subjects (All):
- SAS (Computer file).
- Failure time data analysis--Data processing.
- Failure time data analysis.
- Survival analysis (Biometry)--Data processing.
- Survival analysis (Biometry).
- Physical Description:
- viii, 292 pages : illustrations ; 28 cm
- Place of Publication:
- Cary, NC : SAS Institute, [1995]
- Summary:
- Analyzing survival data with the SAS System? Easy to read and comprehensive, this guide is ideal for biomedical and social science researchers. Written for the person 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 become sophisticated users of survival analysis.
- Contents:
- What is Survival Data? 2
- Why Use Survival Analysis? 4
- Approaches to Survival Analysis 5
- Computing Notes 7
- Chapter 2 Basic Concepts of Survival Analysis 9
- Censoring 9
- Describing Survival Distributions 14
- Interpretations of the Hazard Function 17
- Some Simple Hazard Models 19
- The Origin of Time 22
- Data Structure 25
- Chapter 3 Estimating and Comparing Survival Curves with PROC LIFETEST 29
- The Kaplan-Meir Method 30
- Testing for Differences in Survivor Functions 36
- The Life-Table Method 41
- Life Tables from Grouped Data 49
- Testing for the Effects of Covariates 52
- Log Survival and Smoothed Hazard Plots 56
- Chapter 4 Estimating Parametric Regression Models with PROC LIFEREG 61
- The Accelerated Failure Time Model 62
- Alternative Distributions 66
- Categorical Variables and the CLASS Statement 78
- Maximum Likelihood Estimation 79
- Hypothesis Tests 85
- Goodness-of-Fit Tests with the Likelihood-Ratio Statistic 88
- Graphical Methods for Evaluating Model Fit 91
- Left Censoring and Interval Censoring 97
- Generating Predictions and Hazard Functions 101
- The Piecewise Exponential Model 104
- Chapter 5 Estimating Cox Regression Models with PROC PHREG 111
- The Proportional Hazards Model 113
- Partial Likelihood 114
- Tied Data 127
- Time-Dependent Covariates 138
- Cox Models with Nonproportional Hazards 154
- Interactions with Time as Time-Dependent Covariates 155
- Nonproportionality via Stratification 158
- Left Truncation and Late Entry into the Risk Set 161
- Estimating Survivor Functions 165
- Residuals and Influence Statistics 173
- Testing Linear Hypotheses with the TEST Statement 181
- Chapter 6 Competing Risks 185
- Type-Specific Hazards 186
- Time in Power for Leaders of Countries: Example 189
- Estimates and Tests without Covariates 190
- Covariate Effects via Cox Models 195
- Accelerated Failure Time Models 200
- An Alternative Approach to Multiple Event Types 206
- Chapter 7 Analysis of Tied or Discrete Data with the LOGISTIC, PROBIT, and GENMOD Procedures 211
- The Logit Model for Discrete Time 212
- The Complementary Log-Log Model for Continuous-Time Processes 216
- Data with Time-Dependent Covariates 219
- Issues and Extensions 223
- Chapter 8 Heterogeneity, Repeated Events, and Other Topics 233
- Unobserved Heterogeneity 233
- Repeated Events 236
- Generalized R[superscript 2] 247
- Sensitivity Analysis for Informative Censoring 249
- Chapter 9 A Guide for the Perplexed 253
- How to Choose a Method 253
- Appendix 1 Macro Programs 259
- The SMOOTH Macro 259
- The LIFEHAZ Macro 261
- The PREDICT Macro 263
- The WLW Macro 264
- Appendix 2 Data Sets 269
- The MYEL Data Set: Myelomatosis Patients 269
- The RECID Data Set: Arrest Times for Released Prisoners 270
- The STAN Data Set: Stanford Heart Transplant Patients 271
- The BREAST Data Set: Survival Data for Breast Cancer Patients 272
- The JOBDUR Data Set: Durations of Jobs 272
- The ALCO Data Set: Survival of Cirrhosis Patients 272
- The LEADERS Data Set: Time in Power for Leaders of Countries 273
- The RANK Data Set: Promotions in Rank for Biochemists 274
- The JOBMULT Data Set: Repeated Job Changes 275.
- Notes:
- Includes index.
- Includes bibliographical references: pages 277-281.
- ISBN:
- 155544279X
- 9781555442798
- OCLC:
- 1170611070
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