Product Description

Includes thorough treatment of logistic and Poisson regression.
∗ Introduction to generalized estimating questions.
∗ Numerous examples in fields ranging from biology and biopharmaceuticals to engineering and quality assurance.
∗ Provides guidance in using widely available software to illustrate all aspects of model–fitting, inference, and diagnostic testing.

Product Details

• Amazon Sales Rank: #1051784 in Books
• Published on: 2001-12-21
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 424 pages

Review
"The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities." (Technometrics, Vol. 44, No. 3, August 2002)

"...fulfills the need for an introductory textbook on the generalized linear model..." (Quarterly of Applied Mathematics, Vol. LX, No. 2, June 2002)

"I recommend...to anyone that has an interest...an excellent reference for both the practitioner and the academic alike...the organization, notation, and illustrative examples are well thought out, making this a fun text to read." (IIE Transactions in Operations Engineering)

"...recommended for students, engineers, scientists, and statisticians who want to familiarize themselves with generalized linear models." (Mathematical Reviews, 2002j)

"...an excellent, up–to–date introduction to the field...easily used as a user guide...those less mathematically minded have no need to fear this book... I recommend this book to you all and am delighted to have had the opportunity to review it." (Statistical Methods in Medical Research, Vol. 11, 2002)

"...a good textbook a good reference..." (The American Statistician, Vol. 57, No. 1, February 2003)

Review
"...fulfills the need for an introductory textbook on the generalized linear model..." (Quarterly of Applied Mathematics, Vol. LX, No. 2, June 2002)

"...recommended for students, engineers, scientists, and statisticians who want to familiarize themselves with generalized linear models." (Mathematical Reviews, 2002j)

"...an excellent, up–to–date introduction to the field...easily used as a user guide...those less mathematically minded have no need to fear this book... I recommend this book to you all and am delighted to have had the opportunity to review it." (Statistical Methods in Medical Research, Vol. 11, 2002)

"...a good textbook a good reference..." (The American Statistician, Vol. 57, No. 1, February 2003)

From the Back Cover
A comprehensive introduction to generalized linear models, including logistic and Poisson regression

This volume presents a thorough introductory treatment of generalized linear models (GLM). It features useful examples of GLMs at work in a variety of settings ranging from applications in biology and biopharmaceuticals, to engineering and quality assurance.

The authors review the types of problems that support the use of GLMs, then provide an overview of many of the basic concepts of multiple linear regression and nonlinear regression. Fundamental concepts such as least squares and the maximum likelihood estimation procedure are discussed. Confidence intervals estimation, hypothesis testing procedures, and model diagnostic checking techniques such as residual plotting and influence diagnostics are also presented in detail. Further coverage includes:
∗ Model fitting, inference, and diagnostics for nonlinear regression
∗ Coverage of logistic and Poisson regression
∗ Vivid illustrations of model fitting, inference, and diagnostic checking using SAS PROC GENMOD and S–PLUS software
∗ Introduction to generalized estimating equations (GEEs)

Generalized Linear Models provides an in–depth introduction to the subject for graduate students in regression courses and for engineers, scientists, and statisticians who must understand and apply GLMs in their work.