Primer of Applied Regression & Analysis of Variance [Hardcover]

Stanton Glantz (Author), Bryan Slinker (Author)

Book Description

ISBN-10: 0071360867 | ISBN-13: 978-0071360869 | Publication Date: October 25, 2000 | Edition: 2

Applicable for all statistics courses or practical use, teaches how to understand more advanced multivariate statistical methods, as well as how to use available software packages to get correct results. Study problems and examples culled from biomedical research illustrate key points. New to this edition: broadened coverage of ANOVA (traditional analysis of variance), the addition of ANCOVA (analysis of Co-Variance); updated treatment of available statistics software; 2 new chapters (Analysis of Variance Extensions and Mixing Regression and ANOVA: ANCOVA). (20010101)

Editorial Reviews

Review

This is a solid reference work. Biostatisticians and epidemiologists will find it useful. 3 Stars."--Doody's Review Service (Doody's )

From the Back Cover

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 material NEW 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

See all Editorial Reviews

Product Details

• Hardcover: 949 pages
• Publisher: McGraw-Hill Medical; 2 edition (October 25, 2000)
• Language: English
• ISBN-10: 0071360867
• ISBN-13: 978-0071360869
• Product Dimensions: 9.3 x 7.6 x 2 inches
• Shipping Weight: 4.1 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (3 customer reviews)
• Amazon Best Sellers Rank: #438,155 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

11 of 11 people found the following review helpful:

5.0 out of 5 stars The best advanced statistics book for biologists, May 30, 1998

By 

[e-mail] (Ridgewood, New Jersey) - See all my reviews

This review is from: Primer of Applied Regression and Analysis of Variance (Hardcover)

Like all advanced stats books, this one has mathematical rigor and plenty of examples. But unlike the others, this one is written from the point of view of a biologist. You won't just learn the math, you'll learn how to make sense of the results. The title is a bit misleading. This is not a "primer" of statistics. But once you've learned the basic principles of statistics, this is THE book to learn about various kinds of ANOVAS and regressions.

11 of 12 people found the following review helpful:

5.0 out of 5 stars The best second book of statistics for biologists., November 13, 2000

By 

Harvey Motulsky (Seattle, WA USA) - See all my reviews
(REAL NAME)   

This review is from: Primer of Applied Regression & Analysis of Variance (Hardcover)

Once you've learned the basic principles of statistics, how can a biologist learn more advanced techniques? Many books focus on math rather than on understanding concepts. Other books are too narrow -- discussing only a single method. And books that focus on multiple regression and ANOVA tend to have examples from psychology and social sciences. Glantz and Slinker do a great job of explaining the principles of multiple regression, analysis of variance, and analysis of covariance. The focus is not on mathematical proofs, but rather on making sense of the results in the context of biological and medical research.

This book also has excellent chapters on linear regression, nonlinear regression (curve fitting) and logistic and proportional hazards regression (regression when the outcome is an either-or binary variable).

New to the second edition are a chapter on analysis of covariance, more extensive discussions of multiple comparisons methods, and a discussion of Cox proportional hazards regression for analyses of survival data.

The title is a bit misleading. This is not a "primer" of statistics. But once you've learned the basic principles of statistics, this is THE book for biologists to learn about various kinds of ANOVAS and regressions.

3 of 3 people found the following review helpful:

5.0 out of 5 stars Outstanding, January 30, 2006

By 

Brant Inman (Somewhere out there) - See all my reviews
(REAL NAME)   

This review is from: Primer of Applied Regression & Analysis of Variance (Hardcover)

I looked at several options for a regression textbook that would be both understandable and relatively complete for my introduction to the topic. This book won hands down. The authors keep it simple and use a wide variety of examples to get the point across. I felt that the sections on logistic and Cox regression could have been a bit better, but these subjects are best learned by dedicated textbooks such as Hosmer and Lemeshow and Collett.

I think that this may be the best introductory regression book out there.