The analysis of covariance and alternatives: statistical methods for experiments, quasi-experiments, and single-case studies

Excellent discussions of assumptions, comprehensive interpretations of results, and numerous comparisons of various multiple comparison procedures are the hallmarks of this book on analysis of covariance. Detailed calculations are presented throughout with sensitivity to problems of multiple inference. The author extensively discusses the problems caused by violation of the mathematicalassumptions and he extends an invaluable amount of detail on examples of interpretations. The synthesis of the literature is a contribution in and of itself. Written for the applied researcher, the book also finds a niche among experimental design and statistical regression courses in a variety of fields from engineering to the social sciences as supplemental reading. Key features include: Detailed descriptions of assumptions, the consequences of violating assumptions, and alternative procedures to follow are explained throughout the book Interpretation issues associated with each experimental design are clearly andstraightforwardly discussed Easily understood descriptions of complex analyses such as multiple covariate analysis, multivariate ANCOVA, rank ANCOVA, the Johnson-Neyman procedure, and nonlinear ANCOVA, among many others, are exploited to the fullest New methods including quasi-ANCOVA, robust analysis of observational studies, and analysis of simple and complex single-case designs Chapter recommendations, summaries, and software discussions have been added to the new edition INDICE: Part I. Basic Experimental Design and Analysis. Chapter 1. Review of Basic Statistical Methods for Randomized Two-Group Designs. Chapter 2. Review of Simple Correlated Samples Designs and Analyses. Chapter 3. Review of ANOVA for One-Factor Randomized Groups, Randomized Block, and Repeated Measures Designs. Part II. Essentials of Regression Analysis. Chapter 4. Simple Regression Analysis. Chapter 5. Overview of Multiple Linear Regression Analysis. Part III. Essentials of Simple and Multiple ANCOVA. Chapter 6. Introduction to ANCOVA. Chapter 7. ANCOVA through Regression. Chapter 8. Assumptions. Chapter 9. Multiple Comparison Procedures. Chapter 10. Multiple ANCOVA. Part IV. Alternatives for Assumption Departures. Chapter 11. Johnson-Neyman and Picked-Points Solutions for Heterogeneous Regression. Chapter 12. Nonlinear ANCOVA. Chapter 13. Quasi-ANCOVA: When Treatments Affect Covariates. Chapter 14. Robust ANCOVA/Robust Picked-Points. Chapter 15. ANCOVA for Dichotomous Dependent Variables. Chapter 16. Designs with Ordered Treatments and No Covariates. Chapter 17. ANCOVA for Ordered Treatments Designs. Part V. Single-Case Designs. Chapter 18. Simple Single-Case AB Designs. Chapter 19. Examples of the Analysis of AB Designs. Chapter 20. Reversal Designs. Chapter 21. Multiple Baseline Designs. Part VI. ANCOVA Extensions. Chapter 22. Power Estimation. Chapter 23. Randomized Block Design ANCOVA. Chapter 24. Two-Factor Designs. Chapter 25. Randomized Pretest-Posttest Designs. Chapter 26. Multiple Dependent Variables. Part VII. Quasi-Experiments and Misconceptions. Chapter 27. Measurement Error Correction. Chapter 28. Design and Analysis of Observational Studies. Chapter 29. Common ANCOVA Misconceptions. Chapter 30. Uncontrolled Clinical Trials. Appendix. Statistical Tables. References. Index.

• ISBN: 978-0-471-74896-0
• Editorial: John Wiley & Sons
• Encuadernacion: Cartoné
• Páginas: 480
• Fecha Publicación: 05/08/2011
• Nº Volúmenes: 1
• Idioma: Inglés