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A Primer on Regression Artifacts
Contributor(s): Campbell, Donald T. (Author), Kenny, David A. (Author)
ISBN: 1572308591     ISBN-13: 9781572308596
Publisher: Guilford Publications
OUR PRICE:   $37.05  
Product Type: Paperback - Other Formats
Published: December 2002
Qty:
Temporarily out of stock - Will ship within 2 to 5 weeks
Annotation: 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.

Additional Information
BISAC Categories:
- Psychology | Clinical Psychology
- Medical | Mental Health
- Psychology | Social Psychology
Dewey: 519.536
LCCN: 99023003
Series: Methodology in the Social Sciences
Physical Information: 0.65" H x 4.94" W x 9.94" (0.74 lbs) 202 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
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.