Modeling Individual Differences in Unfolding Preference Data: A Restricted Latent Class Approach
- 1 September 1990
- journal article
- Published by SAGE Publications in Applied Psychological Measurement
- Vol. 14 (3) , 257-269
- https://doi.org/10.1177/014662169001400304
Abstract
A latent class scaling approach is presented for modeling paired comparison and "pick-any/t" data obtained in a preference study. Although the latent class part of the model identifies homogene ous subgroups that are characterized by their choice probabilities for a set of alternatives, the scaling part of the model describes the single peakedness structure of the choice data. Proce dures are suggested for examining the unfolding struc ture in an unrestricted latent class solution. Two applications are presented to illustrate the technique. In the first application, scaling solutions obtained from a latent class scaling model and a marginal maximum likelihood latent trait model are com pared.Keywords
This publication has 21 references indexed in Scilit:
- A Probabilistic IRT Model for Unfolding Preference DataApplied Psychological Measurement, 1989
- Constrained latent class models: Some further applications†British Journal of Mathematical and Statistical Psychology, 1989
- The Application of an Unfolding Model of the PIRT Type to the Measurement of AttitudeApplied Psychological Measurement, 1988
- An Ordinal I Scaling Method for Questionnaire and Other Ordinal I DataApplied Psychological Measurement, 1988
- Constructing MDS Joint Spaces from Binary Choice Data: A Multidimensional Unfolding Threshold Model for Marketing ResearchJournal of Marketing Research, 1987
- Simple and Weighted Unfolding Threshold Models for the Spatial Representation of Binary Choice DataApplied Psychological Measurement, 1986
- Constrained latent class models: Theory and applicationsBritish Journal of Mathematical and Statistical Psychology, 1985
- A Latent Class Model for Rating DataPsychometrika, 1985
- A General Framework for using Latent Class Analysis to Test Hierarchical and Nonhierarchical Learning ModelsPsychometrika, 1983
- Some Models for the Analysis of Association in Multiway Cross-Classifications Having Ordered CategoriesJournal of the American Statistical Association, 1982