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Applied regression analysis and generalized linear models
Applied regression analysis, linear models, and related methods
- Author / Creator
- Available as
- Physical
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- Creator
- John Fox
- Format
- Books
- Language
- English
- Publication
-
- Second edition
- Los Angeles : Sage, [2008]
- ©2008
- Physical Details
-
- xxi, 665 pages : illustrations ; 26 cm
- ISBNs
- 9780761930426, 0761930426
- OCLC
- ocn176927374
- Rev. ed. of: Applied regression analysis, linear models, and related methods, c1997.
- Includes bibliographical references (pages 638-647) and indexes.
- Statistical models and social science -- What is regression analysis? -- Examining data -- Transforming data -- Linear least-squares regression -- Statistical inference for regression -- Dummy-variable regression -- Analysis of variance -- Statistical theory for linear models -- The vector geometry of linear models -- Unusual and influential data -- Diagnosing non-normality, nonconstant error variance, and nonlinearity -- Collinearity and its purported remedies -- Logit and probit models for categorical response variables -- Generalized linear models -- Time-series regression and generalized least squares -- Nonlinear regression -- Nonparametric regression -- Robust regression -- Missing data in regression models -- Bootstrapping regression models -- Model selection, averaging, and validation
Subjects
- Regression analysis.
- Linear models (Statistics)
- Social sciences -- Statistical methods.
- Models, Theoretical.
Medical Subject Heading
- Regression Analysis.
Medical Subject Heading
- Statistics as Topic.
Medical Subject Heading