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 Statistical Group Comparison
ISBN: 978-0-471-38646-9
Hardcover
212 pages
April 2002
US $160.00
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Preface.
1. Introduction.
1.1 Rationale for Statistical Comparison.
1.2 Comparative Research in the Social Sciences.
1.3 Focus of the Book.
1.4 Outline of the Book.
2. Statistical Foundation for Comparison.
2.1 A System for Statistical Comparison.
2.2 Test Statistics.
2.3 What to Compare?
3. Comparison in Linear Models.
3.1 Introduction.
3.2 An Example.
3.3 Some Preliminary Considerations.
3.4 The Linear Model.
3.5 Comparing Two Means.
3.6 ANOVA.
3.7 Multiple Comparison Methods.
3.8 ANCOVA.
3.9 Multiple Linear Regression.
3.10 Regression Decomposition.
3.11 Which Linear Method to Use?
4. Nonparametric Comparison.
4.1 Nonparametric Tests.
4.2 Resampling Methods.
4.3 Relative Distribution Methods.
5. Comparison of Rates.
5.1 The Data.
5.2 Standardization.
5.3 Decomposition.
6. Comparison in Generalized Linear Models.
6.1 Introduction.
6.2 Comparing Generalized Linear Models.
6.3 A Logit Model Example.
6.4 A Hazard Rate Model Example.
6.A Data Used in Section 6.4.
7. Additional Topics of Comparison in Generalized Linear Models.
7.1 Introduction.
7.2 GLM for Matched Case-Control Studies.
7.3 Dispersion Heterogeneity.
7.4 Bayesian Generalized Linear Models.
7.A The Data for the n : m Design.
8. Comparison in Structural Equation Modeling.
8.1 Introduction.
8.2 Statistical Background.
8.3 Mean and Covariance Structures.
8.4 Group Comparison in SEM.
8.5 An Example.
8.A Examples of Computer Program Listings.
9. Comparison with Categorical Latent Variables.
9.1 Introduction.
9.2 Latent Class Models.
9.3 Latent Trait Models.
9.4 Latent Variable Models for Continuous Indicators.
9.5 Casual Models with Categorical Latent variables.
9.6 Comparison with Categorical Latent Variables.
9.7 Examples.
9.A Software for Categorical Latent Variables.
9.B Computer Program Listings for the Examples.
10. Comparison in Multilevel Analysis.
10.1 Introduction.
10.2 An Introduction to Multilevel Analysis.
10.3 The Basics of the Linear Multilevel Model.
10.4 The Basics of the Generalized Linear Multilevel Model.
10.5 Group as an External Variable in Multilevel Analysis.
10.6 The Relation between Multilevel Analysis and Group Comparison.
10.7 Multiple Membership Models.
10.8 Summary.
10.A Software for Multilevel Analysis.
10.B SAS Program Listings for GLMM Examples.
References.
Index.
1. Introduction.
1.1 Rationale for Statistical Comparison.
1.2 Comparative Research in the Social Sciences.
1.3 Focus of the Book.
1.4 Outline of the Book.
2. Statistical Foundation for Comparison.
2.1 A System for Statistical Comparison.
2.2 Test Statistics.
2.3 What to Compare?
3. Comparison in Linear Models.
3.1 Introduction.
3.2 An Example.
3.3 Some Preliminary Considerations.
3.4 The Linear Model.
3.5 Comparing Two Means.
3.6 ANOVA.
3.7 Multiple Comparison Methods.
3.8 ANCOVA.
3.9 Multiple Linear Regression.
3.10 Regression Decomposition.
3.11 Which Linear Method to Use?
4. Nonparametric Comparison.
4.1 Nonparametric Tests.
4.2 Resampling Methods.
4.3 Relative Distribution Methods.
5. Comparison of Rates.
5.1 The Data.
5.2 Standardization.
5.3 Decomposition.
6. Comparison in Generalized Linear Models.
6.1 Introduction.
6.2 Comparing Generalized Linear Models.
6.3 A Logit Model Example.
6.4 A Hazard Rate Model Example.
6.A Data Used in Section 6.4.
7. Additional Topics of Comparison in Generalized Linear Models.
7.1 Introduction.
7.2 GLM for Matched Case-Control Studies.
7.3 Dispersion Heterogeneity.
7.4 Bayesian Generalized Linear Models.
7.A The Data for the n : m Design.
8. Comparison in Structural Equation Modeling.
8.1 Introduction.
8.2 Statistical Background.
8.3 Mean and Covariance Structures.
8.4 Group Comparison in SEM.
8.5 An Example.
8.A Examples of Computer Program Listings.
9. Comparison with Categorical Latent Variables.
9.1 Introduction.
9.2 Latent Class Models.
9.3 Latent Trait Models.
9.4 Latent Variable Models for Continuous Indicators.
9.5 Casual Models with Categorical Latent variables.
9.6 Comparison with Categorical Latent Variables.
9.7 Examples.
9.A Software for Categorical Latent Variables.
9.B Computer Program Listings for the Examples.
10. Comparison in Multilevel Analysis.
10.1 Introduction.
10.2 An Introduction to Multilevel Analysis.
10.3 The Basics of the Linear Multilevel Model.
10.4 The Basics of the Generalized Linear Multilevel Model.
10.5 Group as an External Variable in Multilevel Analysis.
10.6 The Relation between Multilevel Analysis and Group Comparison.
10.7 Multiple Membership Models.
10.8 Summary.
10.A Software for Multilevel Analysis.
10.B SAS Program Listings for GLMM Examples.
References.
Index.
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