Biomedical and social science researchers who want to analyze survival data with SAS will find just what they need with Paul Allison's easy-to-read and comprehensive guide. Written for the reader with a modest statistical background and minimal knowledge of SAS software, Survival Analysis Using SAS: A Practical Guide teaches many aspects of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical resource, 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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Biomedical and social science researchers who want to analyze survival data with SAS will find just what they need with Paul Allison's easy-to-read and comprehensive guide. Written for the reader with a modest statistical background and minimal knowledge of SAS software, Survival Analysis Using SAS: A Practical Guide teaches many aspects of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical resource, 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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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