A Step-by-Step Approach to Using SAS® for Univariate & Multivariate Statistics, Second Edition
by Norm O’Rourke; Larry Hatcher; Edward J. Stepanski
Categorical Data Analysis Using The SAS® System, 2nd Edition
by Maura E. Stokes; Charles S. Davis; Gary G. Koch
The Little SAS® Book: A Primer, Third Edition
by Lora D. Delwiche; Susan J. Slaughter
Head First Statistics
by Dawn Griffiths
The Little SAS® Book: A Primer, Third Edition
by Lora D. Delwiche; Susan J. Slaughter
SAS® For Dummies®
by Stephen McDaniel; Chris Hemedinger
Real-world problems and data sets are the backbone of Ravindra Khattree and Dayanand Naik's Applied Multivariate Statistics with SAS Software, Second Edition, which provides a unique approach to the topic, integrating statistical methods, data analysis, and applications. Now extensively revised, the book includes new information about mixed effects models, applications of the MIXED procedure, regression diagnostics with the corresponding IML procedure code, and covariance structures. The authors' approach to the information will aid professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding high-resolution output accompany sample problems, and clear explanations of SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples.
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Based on 2 Ratings
nice text that teaches multivariate analysis and SAS also - 2008-02-09
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I wrote a book on bootstrap methods at the same time that Peter Hall was writing his. He kindly sent me an advance copy of the manuscript. This enabled me to incorporate some very useful information in my book. The material is advanced and rigorous. However the asymptotic results for Edgeworth and Cornish-Fisher expansions provide important insight into the advantages of bootstrap and the special modifications such as bootstrap iteration and various other bootstrap variants for confidence intervals including Efron's BCa method. It is well written but requires a good mathematical background and knowledge of advanced probability would be helpful. It is not easy reading even for Ph.D students and postdoctoral researchers but is certainly worth the effort.
Very Nice Introduction to Multivariate Analysis using SAS - 2000-02-10
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The authors gave a short tutorial on the book at the Deming conference last year. I enjoyed the presentation and the book which is not expensive was discounted. I met both authors. They are experts in multivariate analysis having studied under C. R. Rao at Pittsburgh. The book provides lots of SAS code and does a good job of explaining how to set-up the analysis in SAS which would not be straightforward from the SAS manuals. The authors discuss diagnostics and with most concepts they explain them first for univariate problems and then show you how it is extended to the multivariate case. It is also one of the few books that deals with multivariate outliers. Outliers can be difficult to detect in regression and high dimensional multivariate data. I have some research experience in the area of outlier detection and can appreciate the way the authors deal with it.
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