Regression diagnostics : an introduction / John Fox.

Format:

Book

Author/Creator:

Fox, John, 1947- author.

Series:

Quantitative applications in the social sciences ; no. 79.

Quantitative applications in the social sciences ; volume 79

Language:

English

Subjects (All):

Regression analysis.

Social sciences--Statistical methods.

Social sciences.

Physical Description:

xv, 151 pages : illustrations ; 22 cm.

Edition:

Second edition.

Place of Publication:

Thousand Oaks, California : SAGE Publications, Inc., [2020]

Summary:

"Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (straight-line) relationship between the response and an explanatory variable, is the assumption of linearity warranted? Regression diagnostics not only reveal deficiencies in a regression model that has been fit to data but in many instances may suggest how the model can be improved. The Second Edition of this bestselling volume by John Fox considers two important classes of regression models: the normal linear regression model (LM), in which the response variable is quantitative and assumed to have a normal distribution conditional on the values of the explanatory variables; and generalized linear models (GLMs) in which the conditional distribution of the response variable is a member of an exponential family. R code for examples within the text can be found on an accompanying website"-- Provided by publisher.

Contents:

Introduction

The linear regression model : review

Examining and transforming regression data

Unusual data : outliers, leverage, and influence

Nonnormality and nonconstant error variance

Nonlinearity

Collinearity

Diagnostics for generalized linear models

Concluding remarks.

Notes:

Includes bibliographical references (pages 144-146) and index.

ISBN:

9781544375229

1544375220

OCLC:

1123182103