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https://www.um.edu.mt/library/oar/handle/123456789/19187
Title: | Latent class mixture models for analyzing rating responses |
Authors: | Camilleri, Liberato |
Keywords: | Expectation-maximization algorithms Monte Carlo method Latent structure analysis |
Issue Date: | 2009 |
Publisher: | European Technology Institute |
Citation: | Camilleri, L. (2009). Latent class mixture models for analyzing rating responses. 7th Annual Industrial Simulation Conference, Loughborough. 42-46. |
Abstract: | Latent class methodology has been used extensively in market research. In this approach, segment membership and parameter estimates for each derived segment are estimated simultaneously. A popular approach for fitting latent class models to rating responses is to assume mixtures of multivariate conditional normal distributions. An alternative approach is to assume a Proportional Odds model. These two approaches are compared empirically in a Monte Carlo study, assessing segment membership and parameter recovery, goodness of fit and predictive accuracy. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/19187 |
Appears in Collections: | Scholarly Works - FacSciSOR |
Files in This Item:
File | Description | Size | Format | |
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OA Conference paper - Latent Class Mixture models for analyzing Rating Responses.1.pdf | Latent class mixture models for analyzing rating responses | 99.23 kB | Adobe PDF | View/Open |
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