Applicable for all statistics courses or practical use, this book teaches how to understand more advanced multivariate statistical methods as well as how to use available software packages to get correct results. With clear and entertaining writing style, it demystifies a very dry, difficult subject. Study problems at the end of each chapter and examples culled from biomedical research illustrate key points.
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Stanton Glantz is Professor of Medicine and Director of the Center for Tobacco Control Research and Education at the University of California San Francisco, where he conducts research on tobacco control and cardiology. He is author or co-author of over 300 scientific papers and nine books in addition to Primer of Biostatistics, 7th ed. (McGraw-Hill, 2012) and Primer of Applied Regression & Analysis of Variance, 2nd ed. (McGraw-Hill, 2001). He wrote the first major review (published in Circulation) which identified involuntary smoking as a cause of heart disease, and the landmark July 19, 1995 issue of JAMA on the Brown and Williamson documents, which showed that the tobacco industry knew 30 years ago that nicotine is addictive and that smoking causes cancer. His work has attracted considerable attention from the tobacco industry, which has sued the University of California twice (unsuccessfully) in an effort to stop Professor Glantz's work.
Demystifies the Use of Advanced Statistcal Methods
Unlike other texts, Primer of Applied Regression & Analysis of Variance teaches both how to understand more advanced multivariate statistical methods, as well as how to use statistical software to get the correct results. This new edition offers the modern, intuitive approaches that won the first edition a wide following, while adding traditional methods for complete coverage of applied statistical methods.
FEATURES:
*Reader-friendly style that makes complicated material approachable and usable
*Practical guidelines for the correct application of statistical software
*Examples from biological and health sciences research that clarify key points
*End-of-chapter study problems that quickly test mastery of the materialNEW IN THIS EDITION
*Expanded coverage of traditional ANOVA (analysis of variance)
*Expanded coverage of ANOVA extensions, assumptions, and workarounds for "problem" data
*Cox proportional hazard models
*Expanded coverage of repeated measures
*New examples from biological and health sciences research
*Expanded and revised coverage of statistical software
*Web site (http:www.vetmed.wsu.edu/AppliedRegression/) to support statistics instruction and facilitate use of example and problem data sets
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