Constrained latent class analysis: Simultaneous classification and scaling of discrete choice data |
| |
Authors: | Ulf Böckenholt Ingo Böckenholt |
| |
Institution: | (1) University of Karlsruhe, Germany;(2) Department of Psychology, University of Illinois at Urbana-Champaign, 603 East Daniel Street, 61820 Champaign, IL |
| |
Abstract: | A reparameterization of a latent class model is presented to simultaneously classify and scale nominal and ordered categorical choice data. Latent class-specific probabilities are constrained to be equal to the preference probabilities from a probabilistic ideal-point or vector model that yields a graphical, multidimensional representation of the classification results. In addition, background variables can be incorporated as an aid to interpreting the latent class-specific response probabilities. The analyses of synthetic and real data sets illustrate the proposed method.The authors thank Yosiho Takane, the editor and referees for their valuable suggestions. Authors are listed in reverse alphabetical order. |
| |
Keywords: | latent class analysis multidimensional scaling classification |
本文献已被 SpringerLink 等数据库收录! |