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Applied Regression Analysis, Linear Models, and Related Methods

Applied Regression Analysis, Linear Models, and Related Methods - 97 edition

ISBN13: 978-0803945401

Cover of Applied Regression Analysis, Linear Models, and Related Methods 97 (ISBN 978-0803945401)
ISBN13: 978-0803945401
ISBN10: 080394540X
Cover type:
Edition/Copyright: 97
Publisher: Sage Publications, Inc.
Published: 1997
International: No

List price: $115.00

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Applied Regression Analysis, Linear Models, and Related Methods - 97 edition

ISBN13: 978-0803945401

John Fox

ISBN13: 978-0803945401
ISBN10: 080394540X
Cover type:
Edition/Copyright: 97
Publisher: Sage Publications, Inc.

Published: 1997
International: No
Summary

Aimed at researchers and students who want to use linear models for data analysis, John Fox's book provides an accessible, in-depth (and better) treatment of regression analysis, linear models, and closely related methods. Fox incorporates nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences. He begins the book with a concise consideration of the role of statistical data analysis in social research. He next covers graphical methods for examining and transforming data, linear least-squares regression, dummy-variables regression, and analysis of variance. Fox also explores diagnostic methods for discovering whether a linear model fit to data adequately represents the data; extensions to linear least squares, including logit and probit models, time-series regression, nonlinear regression, robust regression, and nonparametric regression; and empirical methods for assessing sampling variation, including the bootstrap and cross-validation. More difficult material is segregated in separate sections and chapters and several appendixes are also included presenting background information.

Scholars, professionals, researchers, and students in research methods, evaluation, education, sociology, and psychology will appreciate the enhanced and thorough treatment that regression analysis, linear models, and other related methods have received by author John Fox.

Author Bio

Fox, John : McMaster University

Table of Contents

I. Preliminaries

1. Statistics and Social Science
2. What Is Regression Analysis?
3. Examining Data
4. Transforming Data

II. Linear Models and Least Squares

5. Linear Least-Squares Regression
6. Statistical Inference for Regression
7. Dummy-Variable Regression
8. Analysis of Variance
9. Statistical Theory for Linear Models
10. The Vector Geometry of Linear Models

III. Linear-Model Diagnostics

11. Unusual and Influential Data
12. Nonlinearity and Other Ills
13. Collinearity

IV. Beyond Linear Least Squares

14. Extending Linear Least Squares
15. Logit and Probit Models
16. Assessing Sampling Variation

Appendixes

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