The robust beauty of improper linear models in decision making.

@article{Dawes1979TheRB,
  title={The robust beauty of improper linear models in decision making.},
  author={Robyn M. Dawes},
  journal={American Psychologist},
  year={1979},
  volume={34},
  pages={571-582}
}
  • R. Dawes
  • Published 1 July 1979
  • Psychology
  • American Psychologist
Proper linear models are those in which predictor variables are given weights in such a way that the resulting linear composite optimally predicts some criterion of interest; examples of proper linear models are standard regression analysis, discriminant function analysis, and ridge regression analysis. Research summarized in Paul Meehl's book on clinical versus statistical prediction—and a plethora of research stimulated in part by that book—all indicates that when a numerical criterion… 

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