METRIC VS. NONMETRIC PROCEDURES FOR MULTIATTRIBUTE MODELING: SOME SIMULATION RESULTS *
- 1 July 1978
- journal article
- Published by Wiley in Decision Sciences
- Vol. 9 (3) , 472-480
- https://doi.org/10.1111/j.1540-5915.1978.tb00736.x
Abstract
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.Keywords
This publication has 10 references indexed in Scilit:
- Comparison of Bayesian and regression approaches to the study of information processing in judgmentPublished by Elsevier ,2004
- How Everyday Life Became VirtualJournal of Consumer Culture, 2001
- A Simple Method for Pairwise Monotone RegressionPsychometrika, 1975
- On the Design of Choice Experiments Involving Multifactor AlternativesJournal of Consumer Research, 1974
- Multi-Attribute Utility Models: A Review of Field and Field-Like StudiesManagement Science, 1974
- Estimating the Weights for Multiple Attributes in a Composite Criterion Using Pairwise JudgmentsPsychometrika, 1973
- Analyzing the Use of Information in Investment Decision Making: A Methodological ProposalThe Journal of Business, 1972
- Five models of clinical judgment: An empirical comparison between linear and nonlinear representations of the human inference processOrganizational Behavior and Human Performance, 1971
- A case study of graduate admissions: Application of three principles of human decision making.American Psychologist, 1971
- Analysis of Factorial Experiments by Estimating Monotone Transformations of the DataJournal of the Royal Statistical Society Series B: Statistical Methodology, 1965