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
- Covers the planning stage of medical studies in detail; several
chapters contain details of sample size estimation
- Illustrates methods of randomisation that might be employed for
clinical trials
- Covers topics that have become of great importance in the 21st
century, including Bayesian methods and multiple imputation
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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