한국청소년정책연구원 도서관

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Survival Amalysis Using SAS: A Practical Guide(Second Edition)

판사항
2nd ed
발행사항
Cary N.C: SAS Institute Inc, 2010
형태사항
324p. , 28cm
서지주기
Includes bibliographical references and index
소장정보
위치등록번호청구기호 / 출력상태반납예정일
이용 가능 (1)
한국청소년정책연구원00021771대출가능-
이용 가능 (1)
  • 등록번호
    00021771
    상태/반납예정일
    대출가능
    -
    위치/청구기호(출력)
    한국청소년정책연구원
책 소개
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.
목차
CONTENTS 1. Introduction 2. Basic Concepts of Survival Analysis 3. Estimating and Comparing Survival Curves with PROC LIFETEST 4. Estimating Parametric Regression Models with PROC LIFEREG 5. Estimating Cox Regression Models with PROC PHREG 6. Competing Risks 7. Analysis of Tied or Discrete Data with PROC LOGISTIC 8. Heterogeneity, Repeated Events, and Other Topics 9. A Guide for the Perplexed Appendix 1 Macro Programs Appendix 2 Data Sets