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Illusions in Regression Analysis

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  • Armstrong, J. Scott

Abstract

Soyer and Hogarth’s article, “The Illusion of Predictability,” shows that diagnostic statistics that are commonly provided with regression analysis lead to confusion, reduced accuracy, and overconfidence. Even highly competent researchers are subject to these problems. This overview examines the Soyer-Hogarth findings in light of prior research on illusions associated with regression analysis. It also summarizes solutions that have been proposed over the past century. These solutions would enhance the value of regression analysis.

Suggested Citation

  • Armstrong, J. Scott, 2011. "Illusions in Regression Analysis," MPRA Paper 81663, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:81663
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    References listed on IDEAS

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    1. Karni, Edi & Shapiro, Barbara, 1980. "Tales of Horror from Ivory Towers," Journal of Political Economy, University of Chicago Press, vol. 88(1), pages 210-212, February.
    2. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
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    8. Armstrong, J. Scott, 1970. "How to avoid exploratory research," MPRA Paper 81666, University Library of Munich, Germany.
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    10. Peter E. Kennedy, 2002. "Sinning in the Basement: What are the Rules? The Ten Commandments of Applied Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 16(4), pages 569-589, September.
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    2. Cogoljević, Dušan & Gavrilović, Milan & Roganović, Miloš & Matić, Ivana & Piljan, Ivan, 2018. "Analyzing of consumer price index influence on inflation by multiple linear regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 941-944.

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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