The Group Calibration Index: a group-based approach for assessing forecasters' expertise when external outcome data are missing [Book Review]
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Theory and Decision 73 (4):671-685 (2012)
The Group Calibration Index (GCI) provides a means of assessing the quality of forecasters’ predictions in situations that lack external feedback or outcome data. The GCI replaces the missing outcome data with aggregated ratings of a well-defined reference group. A simulation study and two experiments show how the GCI classifies forecaster performance and distinguishes between forecasters with restricted information and those with complete information. The results also show that under certain circumstances, where members of the reference group have high-quality information, the new GCI will outperform expert classification that is based on traditional calibration indices.
|Keywords||Group decisions Experts Calibration Uncertainty|
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References found in this work BETA
Emir H. Shuford (1961). Percentage Estimation of Proportion as a Function of Element Type, Exposure Time, and Task. Journal of Experimental Psychology 61 (5):430.
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