Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data. Applied Medical Statistics Using SAS covers the whole range of modern statistical methods used in the analysis of medical data, including regression, analysis of variance and covariance, longitudinal and survival data analysis, missing data, generalized additive models (GAMs), and Bayesian methods. The book focuses on performing these analyses using SAS, the software package of choice for those analysing medical data.
Features
Its breadth and depth, coupled with the inclusion of all the SAS code, make this book ideal for practitioners as well as for a graduate class in biostatistics or public health.
Complete data sets, all the SAS code, and complete outputs can be found on an associated website: http://support.sas.com/amsus
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Geoff Der, Brian S. Everitt
Designed for medical statisticians, this intermediate-level reference explores the use of SAS for analyzing medical data. A chapter on visualizing data includes a detailed account of graphics for investigating data and smoothing techniques. The book also includes chapters on measurement in medicine, epidemiology/observational studies, meta-analysis, Bayesian methods, and handling missing data. The book maintains an example-based approach, with SAS code and output included throughout and available online.
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