Content area

Abstract

Analysis of human judgment and decision making provides useful methodologies for examining the human decision process and substantive results. One such methodology is a lens model analysis. Such a model is used to study how well a model of expert decisions can capture a valid strategy in the decision process. Whether a model of an expert can be more accurate than the expert is addressed. The predictive accuracy (predictive validity) of two linear (statistical) models and two nonlinear models of human experts is compared. The results indicate that nonlinear models can capture factors (valid nonlinear strategy) that contribute to the experts' predictive accuracy. However, linear models cannot capture the valid non-linear strategy as well as nonlinear models. One linear model and two nonlinear models performed as well as the overall average of a group of experts. However, all of the models were outperformed by the most accurate expert by combining validity of decision strategy with characteristics of modeling algorithms, it is possible to explain why certain algorithms perform better than others.

Details

Title
Expert, linear models, and nonlinear models of expert decision making in bankruptcy prediction: A lens model analysis
Author
Kim, Choong Nyoung; McLeod, Raymond, Jr
Pages
189-206
Publication year
1999
Publication date
Summer 1999
Publisher
Taylor & Francis Ltd.
ISSN
07421222
e-ISSN
1557928X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
218909105
Copyright
Copyright M. E. Sharpe Inc. Summer 1999