A Primer on Regression Artifacts

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Edition: 1st
Format: Paperback
Pub. Date: 2002-12-11
Publisher(s): The Guilford Press
List Price: $49.08

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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.

Author Biography

Donald T. Campbell, Ph.D., before his death in 1996 was University Professor of Social Relations, Psychology, and Education at Lehigh University.

Table of Contents

Graphical Introductionp. 1
From the Scatter Plot to the Correlation Coefficientp. 3
The Pair-Link and Galton Squeeze Diagramsp. 12
Backward Predictionp. 16
Biology and Regression toward the Meanp. 17
A Golden Oldie: McNemar's Illustrationp. 18
Conclusionp. 18
Mathematical and Special Casesp. 21
Generalization to the Case with Unequal Means and Variancesp. 21
Formal Definition and Formulasp. 25
Frequently Asked Questions about Regression toward the Meanp. 28
Conclusionp. 35
Regression Artifacts Due to Extreme Group Selectionp. 37
Pre-Post Design and Regression Artifactsp. 37
Examplesp. 40
Conclusionp. 51
Regression Artifacts Due to Matchingp. 53
Detailed Illustration of the Limits of Matchingp. 55
Direction of Biasp. 65
Conclusionp. 66
Regression Artifacts Due to Statistical "Equating"p. 68
Look at the "Treatment Effect" on the Covariatep. 70
Illustration of the Bias in Statistical Equatingp. 71
Direction of Biasp. 74
When Statistical Equating Worksp. 78
Alternatives to Statistical Equatingp. 79
Examplesp. 82
Conclusionp. 84
Regression Artifacts in Change Scoresp. 87
Correlations with Change Scoresp. 88
Reliability of Change Scoresp. 90
The Measurement of Changep. 91
Correlates of Changep. 97
Conclusionp. 98
Regression Artifacts in Time-Series Studiesp. 101
The Connecticut Crackdown on Speedingp. 102
The Offset Effect of Psychotherapyp. 105
Time Series of HIV Treatment in Clinical Trialsp. 110
ARIMA Modeling and Regression Artifactsp. 116
Conclusionp. 118
Regression Artifacts in Longitudinal Studiesp. 120
Over-Time Correlational Structurep. 121
Regression Artifacts in Multiwave Studiesp. 131
Conclusionp. 139
Cross-Lagged Panel Correlation Analysisp. 141
What Is CLPC Analysis?p. 141
Complications in CLPC Analysisp. 146
The Rogosa Critiquep. 148
CLPC as a Special Case of the Multitrait-Multimethod Matrix Modelp. 151
Conclusion: What Is to Be Done?p. 153
Conclusionp. 155
Common Sense and Data Analysis: A Brief Epistemological Exegesisp. 155
Time-Reversed Analysisp. 158
Graphical Display of Resultsp. 163
The Importance of Research Designp. 164
Careful Consideration of Plausible Rival Hypothesesp. 165
Regression and Predictionp. 167
Conclusionp. 170
Glossary of Termsp. 173
Glossary of Symbolsp. 179
Dice-Rolling Program and Data Sets Used as Illustrationsp. 181
The Computation of Autocorrelationsp. 183
Referencesp. 185
Indexp. 195
Table of Contents provided by Rittenhouse. All Rights Reserved.

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