Applied Regression Analysis

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This bestseller will help you learn regression-analysis methods that you can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises that you can solve using the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques. Key Feature Numerous examples and exercises illustrate applications to real studies in a wide variety of disciplines. Several advanced topics are presented in a unique, nonmathematical manner. The quantity of computer results throughout the text has been greatly expanded. Computer output has been used to replace material that unnecessarily emphasized numerical calculations. Table of Contents 1. Introduction to Regression Analysis. 2. Straight-line Regression Analysis. 3. The Correlation Coefficient and Straight-line Regression Analysis. 4. The Analysis-of-Variance Table. 5. Multiple Regression Analysis: General Considerations. 6. Testing Hypotheses in Multiple Regression. 7. Correlations: Multiple, Partial, and Multiple Partial. 8. Confounding and Interaction in Regression. 9. Dummy Variables in Regression. 10. Analysis of Covariance and Other Methods for Adjusting Continuous Data. 11. Regression Diagnostics. 12. Polynomial Regression. 13. Selecting the Best Regression Equation. 14. One-Way Analysis of Variance. 15. Randomized Blocks: Special Case of Two-Way ANOVA. 16. Two-Way ANOVA with Equal Cell Numbers. 17. Two-Way ANOVA with Unequal Cell Numbers. 18. The Method of Maximum Likelihood. 19. Logistic Regression Analysis. 20. Polytomous and Ordinal Logistic Regression. 21. Poisson Regression Analysis. 22. Analysis of Correlated Data Part 1: The General Linear Mixed Model. 23. Analysis of Correlated Data Part 2: Random Effects and Other Issues. 24. Sample Size Planning for Linear and Logistic Regression and Analysis of Variance. Appendix A: Tables Appendix B: Matrices and Their Relationship to Regression Analysis Appendix C: Solutions to Selected Exercises Index.