Assessing dependence: Some experimental results

Assessing dependence: Some experimental results

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Article ID: iaor20012561
Country: United States
Volume: 46
Issue: 8
Start Page Number: 1100
End Page Number: 1115
Publication Date: Aug 2000
Journal: Management Science
Authors: , ,
Keywords: decision theory, statistics: decision
Abstract:

Constructing decision- and risk-analysis probability models often requires measures of dependence among variables. Although data are sometimes available to estimate such measures, in many applications they must be obtained by means of subjective judgment by experts. We discuss two experimental studies that compare the accuracy of six different methods for assessing dependence. Our results lead to several conclusions: First, simply asking experts to report a correlation is a reasonable approach. Direct estimation is more accurate than the other methods studied, is not prone to mathematically inconsistent responses (as are some other measures), and is judged to be less difficult than alternate methods. In addition, directly assessed correlations showed less variability than the correlations derived from other assessment methods. Our results also show that experience with the variables can improve performance somewhat, as can training in a given assessment method. Finally, if a judge uses several different assessment methods, an average of the resulting estimates can also lead to better performance.

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