Applied Regression Analysis, Linear Models, and Related Methods

by John D. Fox

An accessible, detailed, and up-to-date treatment of regression analysis, linear models, and closely related methods is provided in this book. Incorporating nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences, the book begins with a consideration of the role of statistical data analysis in social research. It then moves on to cover the following topics: graphical methods for examining and transforming data; linear least-squares regression; dummy-variables regression; analysis of variance; 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

Hardcover

First published February 5, 1997

About the author

John Fox is the Senator William McMaster Professor of Social Statistics at the Department of Sociology at McMaster University in Canada.

Reviews

[Terran M · Rating 4 out of 5]

You need at least one thorough book on linear regression, and Fox is arguably the gold standard, as he's the author of the R "car" package, derived from his Companion to Applied Regression book, which contains the canonical Type II and III Anova implementation, the variable inflation factor function, and other useful tools. I found the writing in this book to be pretty clear overall.

There are newer editions of this book, but frankly linear regression has not changed much in decades, and this edition is available for 1/10 the cost of the latest one.

[Farhan Samir · Rating 1 out of 5]

It's very thorough in its coverage of linear regression and some related methods but it jumps into rather complicated and unintuitive derivations quickly. Gelman's *Data Analysis Using Regression* gives a more practical introduction.

[Jeffrey · Rating 4 out of 5]

QMSS