A study of self-explicated utility models

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Abstract

Two types of utility models were compared on the basis of their ability to predict the subjects' evaluations of hypothetical university faculty members. The models obtained using multiple regression were better predictors than the models obtained using a parameter-eliciting questionnaire, as expected, but the differences were small. An analysis of variance suggested that increasing the number of factors included in the descriptions caused the subjects to be less able to make consistent evaluations even in the small range included in the study, and also suggested that subjects who were required to respond to fewer factors in early trials and more factors in later trials made less consistent evaluations overall than subjects who were required to respond to more factors in early trials and fewer factors in later trials. The data also suggested that the subjects thought that the factors had a more uniform impact on the evaluations than was actually the case.

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