Multiple Comparisons And Multiple Tests Using Sas Second Edition
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Multiple Comparisons and Multiple Tests Using SAS, Second Edition
New and extensively updated for SAS 9 and later, this work provides cutting-edge methods, specialized macros, and proven best bet procedures. The book also discusses the pitfalls and advantages of various methods, thereby helping readers to decide which is the most appropriate for their purposes. 644 pp. Pub. 7/11.
Multiple Comparisons and Multiple Tests Using SAS, Second Edition (Hardcover Edition)
New and extensively updated for SAS 9 and later! Have you ever felt that there was no multiple inference method that fit the particular constraints of your data? Or been overwhelmed by the many choices of procedures? Multiple Comparisons and Multiple Tests Using SAS, Second Edition, written by Peter Westfall, Randall Tobias, and Russell Wolfinger, solves both problems for you by providing cutting-edge methods, specialized macros, and proven "best bet" procedures. The specialized macros and dozens of real-world examples illustrate solutions for a broad variety of problems that call for multiple inferences. The book also discusses the pitfalls and advantages of various methods, thereby helping you decide which is the most appropriate for your purposes. If you are a researcher or scientist in pharmaceuticals, engineering, government, or medicine, you will find many methods applied to real data and examples from your field. The book includes specialized code and explanations throughout. It discusses in detail pairwise comparisons and comparisons with a control. Additional topics include general linear contrasts; multiple comparisons of multivariate means; and multiple inferences with mixed models, discrete data, and survival analysis.
Multiple Comparisons Using R
Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-pro