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R and S-Plus Companion to Applied Regression

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ISBN-10: 0761922806

ISBN-13: 9780761922803

Edition: 2002

Authors: John Fox, John Fox

List price: $69.95
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Description:

`This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. it meets all of the important mechanical needs: each example is given in detail, code and data are freely available, and the nuances of models are given rather than just the bare essentials. It also meets some important theoretical needs: linear models, categorical data analysis, an introduction to applying GLMs, a discussion of model diagnostics and useful instructions on writing customized…    
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Book details

List price: $69.95
Copyright year: 2002
Publisher: SAGE Publications, Incorporated
Publication date: 6/5/2002
Binding: Paperback
Pages: 328
Size: 6.97" wide x 10.00" long x 0.75" tall
Weight: 1.496
Language: English

John Fox is the Senator William McMaster Professor of Social Statistics in the Sociology Department of McMaster University in Hamilton, Ontario, Canada. Professor Fox earned a Ph.D. in sociology from the University of Michigan in 1972. He has delivered numerous lectures and workshops on statistical topics, at such places as the summer program of the Inter-University Consortium for Political and Social Research, the annual meetings of the American Sociological Association, and the Oxford Spring School in Quantitative Methods for Social Research. He has written many articles on statistics, sociology, and social psychology, and is the author of several books on statistics, including most…    

Preface
Introducing R and S-PLUS
S Basics
An Extended Illustration
S Functions for Basic Statistics
Reading and Manipulating Data
Data Input
Working with Data Frames
Matrices, Arrays, and Lists
Data Attributes, Modes, and Classes
Exploring and Transforming Data
Examining Distributions
Examining Relationships
Examining Multivariate Data
Transforming Data
Fitting Linear Models
Linear Least-Squares Regression
Dummy-Variable Regression
Analysis of Variance Models
User-Specified Contrasts*
General Linear Hypotheses*
Data and Confidence Ellipses
More on 1m and Model Formulas
Fitting Generalized Linear Models
The Structure of GLMs
Models for Categorical Responses
Poisson GLMs for Count Data
Odds and Ends
Fitting GLMs by Iterated Weighted Least-Squares*
Diagnosing Problems
Unusual Data
Non-Normal Errors
Non-Constant Error Variance
Nonlinearity
Collinearity and Variable Selection
Diagnostics for Generalized Linear Models
Drawing Graphs
A General Approach to S Graphics
Putting it Together
Effect Displays
Graphics Devices
Writing Programs
Defining Functions
Working With Matrices*
Program Control: Conditionals, Loops, and Recursion
Apply and its Relatives
Object-Oriented Programming in S*
Writing S Programs