[size=120%]Survival Analysis Using SAS: A Practical Guide, Second Edition
By Paul D Allison

• Publisher:   SAS Publishing
• Number Of Pages:   336
• Publication Date:   2010-04-23
• ISBN-10 / ASIN:   1599946408
• ISBN-13 / EAN:   9781599946405

Product 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.



Summary: Great got better
Rating: 5
If you read the reviews of the first edition of this book (Survival Analysis Using SAS: A Practical Guide) you will see that everyone loved it. This edition is even better. The new edition is updated to cover a *LOT* of new functionality. There are new tests, new methods (especially noteworthy are the new Bayesian techniques), and a lot of new graphics. Things that used to be done with custom macros are now built into SAS and Allison covers them with the same clarity as people loved in the first edition.

To get a feel for the updates, the chapter on Kaplan-Meier methods is greatly expanded (don't worry if you don't know what that means he explains both the math and concepts beautifully). In the first edition he showed how to test for differences between three treatment groups but if there were differences in between the groups you could not test to see if group "a" differed from "b" or "b" from "c", etc., and adjust the p-values for multiple comparisons, this edition covers these critical tests (with adjustments for multiple comparison). There is also a lot of new material on graphics, like getting hazard function estimates with confidence intervals.

If you are a biomedical researcher, this book explains both the reasons why you will want to do a test and how to conduct it. Basically Allison makes SAS seem like the best choice for survival analysis.

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