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A Primer on Regression Artifacts | 
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Campbell, Donald T. and David A. Kenny [Foreword by Charles S. Reichardt] |  | | Guilford Publications / Softcover / 2002-12-01 / 1572308591 | | | Research | | price: $32.50 (may be subject to change) | | | 202 pages | | |
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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. --- from the publisher 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
10. 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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