Survival Analysis Using SAS: A Practical Guide, Second Edition

Description

Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul D. Allison, is an accessible, data-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with this fully updated new edition that incorporates the many enhancements in SAS procedures for survival analysis in SAS 9. Although the book assumes only a minimal knowledge of SAS, more experienced users will learn new techniques 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. The main topics presented include censoring, survival curves, Kaplan-Meier estimation, accelerated failure time models, Cox regression models, and discrete-time analysis. Also included are topics not usually covered in survival analysis books, such as time-dependent covariates, competing risks, and repeated events. Survival Analysis Using SAS: A Practical Guide, Second Edition, has been thoroughly updated for SAS 9, and all figures are presented using ODS Graphics. This new edition also documents major enhancements to the STRATA statement in the LIFETEST procedure; includes a section on the PROBPLOT command, which offers graphical methods to evaluate the fit of each parametric regression model; introduces the new BAYES statement for both parametric and Cox models, which allows the user to do a Bayesian analysis using MCMC methods; demonstrates the use of the counting process syntax as an alternative method for handling time-dependent covariates; contains a section on cumulative incidence functions; and describes the use of the new GLIMMIX procedure to estimate random-effects models for discrete-time data. This book is part of the SAS Press program. PREFACE Introduction WHAT IS SURVIVAL ANALYSIS? WHAT IS SURVIVAL DATA? WHY USE SURVIVAL ANALYSIS? APPROACHES TO SURVIVAL ANALYSIS WHAT YOU NEED COMPUTING NOTES Chapter 2: Basic Concepts of Survival Analysis INTRODUCTION CENSORING DESCRIBING SURVIVAL DISTRIBUTIONS INTERPRETATIONS 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 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 MAXIMUM LIKELIHOOD ESTIMATION HYPOTHESIS TESTS GOODNESS-OF-FIT TESTS WITH THE LIKELIHOOD-RATIO STATISTIC LIKELIHOOD-RATIO STATISTIC GRAPHICAL METHODS LEFT CENSORING AND INTERVAL CENSORING GENERATING PREDICTIONS AND HAZARD FUNCTIONS THE PIECEWISE EXPONENTIAL MODEL BAYESIAN ESTIMATION 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 INTERACTIONS NONPROPORTIONALITY LEFT TRUNCATION AND LATE ENTRY INTO THE RISK SET ESTIMATING SURVIVOR FUNCTIONS TESTING LINEAR HYPOTHESES WITH CONTRAST OR TEST STATEMENTS CUSTOMIZED HAZARD RATIOS BAYESIAN ESTIMATION AND TESTING 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 ALTERNATIVE APPROACHES TO MULTIPLE EVENT TYPES CONCLUSION Analysis of Tied or Discrete Data with PROC LOGISTIC INTRODUCTION THE LOGIT MODEL FOR DISCRETE TIME THE COMPLEMENTARY LOG-LOG MODEL FOR CONTINUOUS-TIMEPROCESSES DATA WITH TIME-DEPENDENT COVARIATES ISSUES AND EXTENSIONS CONCLUSION Heterogeneity, Repeated Events, and Other Topics INTRODUCTION UNOBSERVED HETEROGENEITY REPEATED EVENTS GENERALIZED R-Squared SENSITIVITY ANALYSIS FOR INFORMATIVE CENSORING Chapter 9: A Guide for the Perplexed HOW TO CHOOSE A METHOD CONCLUSION Appendix 1: Macro Programs INTRODUCTION THE LIFEHAZ MACRO THE PREDICT MACRO Appendix 2: Data Sets INTRODUCTION THE MYEL DATA SET: MYELOMATOSIS PATIENTS THE RECID DATA SET: ARREST TIMES THE STAN DATA SET: STANFORD HEART TRANSPLANT PATIENTS THE BREAST DATA SET: SURVIVAL DATA THE JOBDUR DATA SET: DURATIONS THE ALCO DATA SET: SURVIVAL CIRRHOSIS PATIENTS THE LEADERS DATA SET: TIME THE RANK DATA SET: PROMOTIONS BIOCHEMISTS THE JOBMULT DATA SET: REPEATED JOB CHANGES REFERENCES REFERENCES Index