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Measurement Errors in Probability Judgments

Author

Listed:
  • Chezy Ofir

    (Hebrew University of Jerusalem, School of Business, Mt. Scopus, Jerusalem 91905, Israel)

  • Srinivas K. Reddy

    (121 Brooks Hall, Terry College of Business, University of Georgia, Athens, Georgia 30602)

Abstract

This paper investigates the psychometric properties of three measures of subjective uncertainty---a zero-to-hundred subjective probability scale and two seven point rating scales. Individual level analysis applied to data obtained from two separate studies suggests that the scales produce fairly similar results: The inter-response mode correlations were high, and individual plots comparing various methods were quite similar. Covariance structure models based on multitrait-multimethod matrices are utilized to assess the reliability and method variance of the scales. The cumulative evidence suggests that rating scales are consistently just as reliable as the subjective probability scale. The probability scale contained significant method error. In fact, the two rating scales were found to have lower systematic method variance and lower random error variance than the subjective probability scale. The paper concludes with a discussion regarding possible explanations of these results and directions for future research.

Suggested Citation

  • Chezy Ofir & Srinivas K. Reddy, 1996. "Measurement Errors in Probability Judgments," Management Science, INFORMS, vol. 42(9), pages 1308-1325, September.
    • Handle: RePEc:inm:ormnsc:v:42:y:1996:i:9:p:1308-1325
    DOI: 10.1287/mnsc.42.9.1308
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    Citations

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    Cited by:

    1. Ofir, Chezy & Mazursky, David, 1997. "Does a Surprising Outcome Reinforce or Reverse the Hindsight Bias?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 69(1), pages 50-57, January.
    2. Lam, K.Y. & Koning, A.J. & Franses, Ph.H.B.F., 2007. "Confidence intervals for maximal reliability of probability judgments," Econometric Institute Research Papers EI 2007-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. J. A. A. Andrade & J. P. Gosling, 2011. "Predicting rainy seasons: quantifying the beliefs of prophets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(1), pages 183-193.

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