Additive Structure in Qualitative Data: An Alternating Least Squares Method with Optimal Scaling Features
Open Access
- 1 December 1976
- journal article
- Published by Cambridge University Press (CUP) in Psychometrika
- Vol. 41 (4) , 471-503
- https://doi.org/10.1007/bf02296971
Abstract
A method is developed to investigate the additive structure of data that (a) may be measured at the nominal, ordinal or cardinal levels, (b) may be obtained from either a discrete or continuous source, (c) may have known degrees of imprecision, or (d) may be obtained in unbalanced designs. The method also permits experimental variables to be measured at the ordinal level. It is shown that the method is convergent, and includes several previously proposed methods as special cases. Both Monte Carlo and empirical evaluations indicate that the method is robust.Keywords
This publication has 19 references indexed in Scilit:
- Regression with Qualitative and Quantitative Variables: An Alternating Least Squares Method with Optimal Scaling FeaturesPsychometrika, 1976
- Sur des méthodes d'optimisation par relaxationRevue française d'automatique informatique recherche opérationnelle. Mathématique, 1973
- Stimulus correlates of area judgments: A psychophysical developmental study.Developmental Psychology, 1971
- Nonmetric Multidimensional Scaling: Recovery of Metric InformationPsychometrika, 1970
- Some Contributions to Maximum Likelihood Factor AnalysisPsychometrika, 1967
- The method of projections for finding the common point of convex setsUSSR Computational Mathematics and Mathematical Physics, 1967
- Constrained minimization methodsUSSR Computational Mathematics and Mathematical Physics, 1966
- Nonmetric Multidimensional Scaling: A Numerical MethodPsychometrika, 1964
- Optimal Scaling for Ordered CategoriesPsychometrika, 1962
- On the prediction of phenomena from qualitative data and the quantification of qualitative data from the mathematico-statistical point of viewAnnals of the Institute of Statistical Mathematics, 1951