Data Analysis A Model Comparison Approach to Regression, ANOVA, and Beyond

ISBN : 9781032572086

Author : Josh Correll

Publisher : Routledge

Year : 2026

Language : English

Type : Book

Description : Preface Introduction to Section A: Statistical Machinery 1. Introduction to Data Analysis 2. Simple Models: Definitions of Error and Parameter Estimates 3. Simple Models: Models of Error and Sampling Distributions 4. Simple Models: Statistical Inferences about Parameter Estimates 5. Statistical Power: Power, Effect Sizes, and Confidence Intervals Summary of Section A Introduction to Section B: Increasingly Complex Models 6. Simple Regression: Models with a Single Continuous Predictor 7. Multiple Regression: Models with Multiple Continuous Predictors 8. Moderated and Nonlinear Multiple Regression models 9. One-Way ANOVA: Models with a Single Categorical Predictor 10. Factorial ANOVA: Models with Multiple Categorical Predictors and Product Terms 11. ANCOVA: Models with Continuous and Categorical Predictors Summary of Section B Introduction to Section C: Violations of Assumptions About Error 12. Repeated-Measures ANOVA: Models with Nonindependent Errors 13. Incorporating Continuous Predictors with Nonindependent Data: Towards Mixed Models 14. Outliers and Ill-Mannered Error 15. Logistic Regression: Dependent Categorical Variables Summary of Section C References Appendix Author Index Subject Index

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