Book Description
Biomedical and social science researchers who want to analyze survival data with the SAS System will find just what they need with this easy-to-read and comprehensive guide. Written for the person with a modest statistical background and minimal knowledge of SAS software, this book teaches many aspects of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical book ensuring that even the uninitiated becomes a sophisticated user 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 such as time-dependent covariates, competing risks, and repeated events. Supports releases 6.09 and higher of SAS software.
Survival Analysis Using the SAS System: A Practical Guide FROM THE PUBLISHER
Analyzing survival data with the SAS System? Easy to read and comprehensive, this guide is ideal for biomedical and social science researchers. Written for the person with a modest statistical background and minimal knowledge of SAS software, this book teaches many aspects 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.
SYNOPSIS
Biomedical and social science researchers who want to analyze survival data with SAS will find just what they need with this easy-to-read and comprehensive guide. Written for the reader with a modest statistical background and minimal knowledge of SAS software, this book teaches many aspects of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical book ensuring that even the uninitiated becomes a sophisticated user 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 such as time-dependent covariates, competing risks, and repeated events.
Paul D. Allison is Professor of Sociology at the University of Pennsylvania where he teaches graduate courses in survival analysis and categorical data analysis. Every summer he teaches a five-day workshop on survival analysis that is attended by researchers from around the United States and Canada. Besides his numerous statistical papers, he has also published extensively on the subject of scientists' careers.
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