Franklin

Regression diagnostics : an introduction / John Fox.

Author/Creator:
Fox, John, 1947- author.
Publication:
Thousand Oaks, California : SAGE Publications, Inc., [2020]
Format/Description:
Book
xv, 151 pages : illustrations ; 22 cm.
Edition:
Second edition.
Series:
Quantitative applications in the social sciences ; no. 79.
Quantitative applications in the social sciences ; volume 79
Status/Location:
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Subjects:
Regression analysis.
Social sciences -- Statistical methods.
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
9781544375212
9781544375205
9781544375199
OCLC:
1123182103