SAS Survival Analysis Techniques for Medical Research

Front Cover
SAS Institute, 2003 - Computers - 230 pages
If you are new to survival analysis or want to expand your capabilities in this area, you'll benefit from Alan Cantor's SAS Survival Analysis Techniques for Medical Research, Second Edition, which presents the theory and methods of survival analysis along with excellent discussions of the SAS procedures used to implement the methods described. New features of the second edition include a discussion of permutation and randomization tests; a discussion of the use of data imputation; an expanded discussion of power for Cox regression; descriptions of the new features of SAS 9, such as confidence bands for the Kaplan-Meier curve; appendixes that cover mathematical and statistical background topics needed in survival analysis; and student exercises. The new features, along with several useful macros and numerous examples, make this a suitable textbook for a course in survival analysis for biostatistics majors and majors in related fields. This book excels at presenting complex ideas in a way that enables those without a strong technical background to understand and apply the concepts and techniques.

About the author (2003)

Alan B. Cantor, a member of the Biostatistics Core at the H. Lee Moffitt Cancer Center and Research Institute, earned his Ph.D. in Mathematics and had an additional two-year post-doctoral fellowship in Biostatistics. A SAS user since 1980, his experience includes extensive use of base SAS, SAS/STAT, the IML procedure, and SAS/GRAPH software. Cantor's work has been published in several prestigious medical journals and in noted scientific and statistical publications such as the New England Journal of Medicine, Journal of the American Medical Association, Journal of Clinical Oncology, Controlled Clinical Trials, and Statistics in Medicine. Cantor continues to teach, write about, and study the methods of survival analysis research.Another BBU title by this author: Extending SAS Survival Analysis Techniques for Medical Research

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