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METRIC VS. NONMETRIC PROCEDURES FOR MULTIATTRIBUTE MODELING: SOME SIMULATION RESULTS *
Author(s) -
Cattin Philippe,
Bliemel Friedhelm
Publication year - 1978
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1978.tb00736.x
Subject(s) - ordinary least squares , metric (unit) , econometrics , statistics , goodness of fit , regression , estimation , regression analysis , mathematics , explained sum of squares , least squares function approximation , computer science , economics , operations management , management , estimator
Nonmetric procedures such a MONANOVA have been developed to estimate attribute utilities with ranked observations. It is argued that the goodness of the estimation procedure is another criterion which favors a metric procedure like Ordinary Least Squares (OLS) Regression. MONANOVA and OLS Regression are compared in their ability to recover attribute utilities with both ranked and scaled observations.