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Survival Analysis Using SAS : A Practical Guide, Second Edition

by
Edition:
2nd
ISBN13:

9781599946405

ISBN10:
1599946408
Format:
Paperback
Pub. Date:
3/29/2010
Publisher(s):
Sas Inst

Customer Reviews

Great book  June 15, 2011
by


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 textbooks, such as time-dependent covariates, competing risks, and repeated events. Basically Allison makes SAS seem like the best choice for survival analysis. This rental textbook was enjoyable to read. I highly recommend it.






Survival Analysis Using SAS : A Practical Guide, Second Edition: 4 out of 5 stars based on 1 user reviews.

Summary

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.

"A complete novice to this subject, I learned survival analysis on the fly from a client who had the utmost confidence in my ability. I practiced due diligence by obsessively double-checking my code and methods against a hodge-podge of references. However, published information was so lacking in substance, consistency, and applicability that I asked her how to set up the censoring variable and produced what is obviously in hindsight an alarming number of staged 2xn frequency tables for quality assurance purposes. With Survival Analysis Using SAS: A Practical Guide, Second Edition, at my disposal, I can make better use of client time-and my energy-by knowing the questions to ask when constructing analyses . . . and to avoid ones that shouldn't ever need to be asked." -Christine Leonard Westgate, Contract Programmer-Analyst, New Hampshire

"Statistical analysts as well as readers with little statistical knowledge can benefit from the book's content. Explanations are clear and concise, providing enough information to give the reader an understanding of survival analysis. Throughout the book, concepts are supported with theory, statistical formulas, and examples. Examples shown are from a variety of fields, allowing readers to transfer methods to their field of study. The book was enjoyable to read. I highly recommend Survival Analysis Using SAS: A Practical Guide, Second Edition." -Diana Suhr, PhD, Statistical Analyst, Office of Budgets and Institutional Analysis, University of Northern Colorado

Author Biography

Paul D. Allison is Professor of Sociology at the University of Pennsylvania, where he teaches graduate courses in statistics. He is the author of Logistic Regression Using the SAS System: Theory and Application, Survival Analysis Using SAS: A Practical Guide, and Fixed Effects Regression Methods for Longitudinal Data Using SAS. Paul has also written numerous statistical papers and published extensively on the subject of scientists' careers. He frequently teaches public short courses on the methods described in his books. You can visit his Web site at www.PaulDAllison.com.


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