專家區間估計中過度自信之研究

A Study of Overconfidence for Expert’s Interval Judgments

王國全(Kuo-Chuan Wang)

指導教授 ： 林希偉

元智大學/管理學院/企業管理學系/碩士(2007年)

https://doi.org/10.6838/YZU.2007.00241

摘要

在決策或風險評估的領域中，專家判斷（expert judgment）是一個被廣為應用的方法。然當過度自信（overconfidence）表現在專家判斷中時，卻可能嚴重影響決策的品質。本研究旨在探討專家機率區間估計中之過度自信差異的來源，然而，為了修正過去相關研究中使用二元變數作為校準衡量所帶來的不穩定性，我們運用專家主觀機率之期望絕對誤差和由真實值所求得之絕對誤差兩者間的比值定義一個連續型的指標作為新的校準衡量，並藉以使用較簡單的線性混合模型（linear mixed model）來詮釋資料。

在新的校準衡量下，我們發現專家之間的變異遠小於問題之間或者真實值所造成的隨機變異，推翻了先前二元校準量測的分析結果。因此，在實務中使用專家機率區間判斷時，運用種子問題來篩選較具專業知識或校準程度較高的專家可得到的效果將十分有限。

關鍵字

過度自信 ； 校準 ； 區間估計 ； 專家判斷

並列摘要

Expert judgment has been widely applied in the field of decision making and risk assessment. However, when overconfidence reveals in the judgment, it might serious affect decision quality. Thus, this study aims at discussing different sources of expert overconfidence in probability interval estimation. To revise the instability which is caused by using binary variables as calibration measuring in previous researches, we define a continuous variable as new calibration measurement by applying the value between EAD (Expected absolute deviation) of experts’ subjective probability and MAD (Mean Absolute Deviation) of realization; further, interpret the data by a simpler liner mixed model.

Under the new calibration measurement, we discover that the variance among experts is less than the random variance among questions or realizations. This result has overthrown the analytic outcome of binary calibration measurement. Thus, to use expert judgment in practice, the effect will be limited by adopting seed questions to select a more professional expert or the one in higher calibration level.

並列關鍵字

Overconfident ； Calibration ； Interval Estimate ； Expert Judgment

參考文獻

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