Logistic Regression: From Introductory to Advanced Concepts and Applications

Logistic Regression: From Introductory to Advanced Concepts and Applications
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DOI:
10.5860/choice.47-0338
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发表时间:
2009-04
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通讯作者:
S. Menard
S. Menard
中科院分区:
其他
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作者:
S. Menard

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Preface Chapter 1. Introduction: Linear Regression and Logistic Regression Chapter 2. Log-Linear Analysis, Logit Analysis, and Logistic Regression Chapter 3. Quantitative Approaches to Model Fit and Explained Variation Chapter 4. Prediction Tables and Qualitative Approaches to Explained Variation Chapter 5. Logistic Regression Coefficients Chapter 6. Model Specification, Variable Selection, and Model Building Chapter 7. Logistic Regression Diagnostics and Problems of Inference Chapter 8. Path Analysis With Logistic Regression (PALR) Chapter 9. Polytomous Logistic Regression for Unordered Categorical Variables Chapter 10. Ordinal Logistic Regression Chapter 11. Clusters, Contexts, and Dependent Data: Logistic Regression for Clustered Sample Survey Data Chapter 12. Conditional Logistic Regression Models for Related Samples Chapter 13. Longitudinal Panel Analysis With Logistic Regression Chapter 14. Logistic Regression for Historical and Developmental Change Models: Multilevel Logistic Regression and Discrete Time Event History Analysis Chapter 15. Comparisons: Logistic Regression and Alternative Models Appendix A: ESTIMATION FOR LOGISTIC REGRESSION MODELS Appendix B: PROOFS RELATED TO INDICES OF PREDICTIVE EFFICIENCY Appendix C: ORDINAL MEASURES OF EXPLAINED VARIATION References Index