Summary: Regression toward the mean is a complex statistical principle that plays a crucial role in any research involving the measurement of change. This primer is designed to help researchers more fully understand this phenomenon and avoid common errors in interpretation. The book presents new methods of graphing regression toward the mean, facilitating comprehension with a wealth of figures and diagrams. Special attention is given to applications related to program or trea
tment evaluation. Numerous concrete examples illustrate the ways researchers all too often attribute effects to an intervention or other causal variable without considering regression artifacts as an alternative explanation for change. Also discussed are instances when problems are actually created, instead of solved, by "correction" for regression toward the mean. Throughout, the authors strive to use nontechnical language and to keep simulations and formulas as accessible as possible.
Summary: Regression toward the mean is a complex statistical principle that plays a crucial role in any research involving the measurement of change. This primer is designed to help researchers more fully understand this phenomenon and avoid common errors in interpretation. The book presents new methods of graphing regression toward the mean, facilitating comprehension with a wealth of figures and diagrams. Special attention is given to applications related to program or treatment evaluation. Numerous concrete examples illustrate the ways researchers all too often attribute effects to an intervention or other causal variable without considering regression artifacts as an alternative explanation for change. Also discussed are instances when problems are actually created, instead of solved, by "correction" for regression toward the mean. Throughout, the authors strive to use nontechnical language and to keep simulations and formulas as accessible as possible. ...show less
Edition/Copyright:99 Cover: Publisher:Guilford Press Year Published: 1999 International: No
"All mental health researchers must read this book, which definitely explores a vital topic. It is a magnificent concluding collaboration between Kenny and the late Campbell, the 20th century's foremost behavioral science methodologist."
"In a world that calls attention to extremes, both good and bad, it is critical that social scientists fully understand regression effects. Campbell and Kenny have produced a book on this topic that is destined to be a classic. Ideally suited for graduate students in the social sciences and for nonexperimental researchers, the book is comprehensive and accessible....Producers as well as critical consumers of empirical information will want this text on their shelves."
--Patrick E. Shrout, PhD, New York University
Publisher Web Site, December, 2004
View Table of Contents
1. Graphical Introduction
From the Scatter Plot to the Correlation Coefficient The Pair-Link and Galton Squeeze Diagrams Backward Prediction Biology and Regression toward the Mean A Golden Oldie: McNemar's Illustration Conclusion
2. Mathematical and Special Cases
Generalization to the Case with Unequal Means and Variances Formal Definition and Formulas Frequently Asked Questions about Regression toward the Mean Conclusion
3. Regression Artifacts Due to Extreme Group Selection
Pre-Post Design and Regression Artifacts Examples Conclusion
4. Regression Artifacts Due to Matching
Detailed Illustration of the Limits of Matching Direction of Bias Conclusion
5. Regression Artifacts Due to Statistical "Equating"
Look at the "Treatment Effect" on the Covariate Illustration of the Bias in Statistical Equating Direction of Bias When Statistical Equating Works Alternatives to Statistical Equating Examples Conclusion
6. Regression Artifacts in Change Scores
Correlations with Change Scores Reliability of Change Scores The Measurement of Change Correlates of Change Conclusion
7.Regression Artifacts in Time-Series Studies
The Connecticut Crackdown on Speeding The Offset Effect of Psychotherapy Time Series of HIV Treatment in Clinical Trials ARIMA Modeling and Regression Artifacts Conclusion
8. Regression Artifacts in Longitudinal Studies
Over-Time Correlational Structure Regression Artifacts in Multiwave Studies Conclusion
9. Cross-Lagged Panel Correlation Analysis
What Is CLPC Analysis Complications in CLPC Analysis The Rogosa Critique CLPC as a Special Case of the Multitrait-Multimethod Matrix Model Conclusion
Common Sense and Data Analysis: A Brief Epistemological Exegesis Time-Reversed Analysis Graphical Display of Results The Importance of Research Design Careful Consideration of Plausible Rival Hypotheses Regression and Prediction
Conclusion Glossary of Terms Glossary of Symbols Appendix A: Dice-Rolling Program and Data Sets Used as Illustrations Appendix B: The Computation of Autocorrelations
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