Redundancy Analysis for Qualitative Variables
- 1 September 1984
- journal article
- Published by Cambridge University Press (CUP) in Psychometrika
- Vol. 49 (3) , 331-346
- https://doi.org/10.1007/bf02306024
Abstract
Redundancy analysis (also called principal components analysis of instrumental variables) is a technique for two sets of variables, one set being dependent of the other. Its aim is maximization of the explained variance of the dependent variables by a linear combination of the explanatory variables. The technique is generalized to qualitative variables; it then gives implicitly a simultaneous ‘optimal’ scaling of the dependent, qualitative variables. Examples are taken from the Dutch Life Situation Survey 1977, using Satisfaction with Life and Happiness as dependent variables. The analysis leads to one well-being scale, defined by the explanatory variables Marital status, Schooling, Income and Activity.Keywords
This publication has 14 references indexed in Scilit:
- Linear Relations among k Sets of VariablesPsychometrika, 1984
- Multivariate methods for quantitative and qualitative dataJournal of Econometrics, 1983
- On the Optimality of the Simultaneous Redundancy TransformationsPsychometrika, 1982
- An Extension of Wollenberg’s Redundancy AnalysisPsychometrika, 1981
- On redundancy in canonical analysis.Psychological Bulletin, 1976
- A Unifying Tool for Linear Multivariate Statistical Methods: The RV- CoefficientJournal of the Royal Statistical Society Series C: Applied Statistics, 1976
- Reduced-rank regression for the multivariate linear modelJournal of Multivariate Analysis, 1975
- In defense of the general canonical correlation index: Reply to Nicewander and Wood.Psychological Bulletin, 1975
- Linear Statistical Inference and its ApplicationsPublished by Wiley ,1973
- A general canonical correlation index.Psychological Bulletin, 1968