A Latent Class Binomial Logit Methodology for the Analysis of Paired Comparison Choice Data: An Application Reinvestigating the Determinants of Perceived Risk

Michel Wedel, Wayne S. DeSarbo

Research output: Contribution to journalArticle

25 Scopus citations

Abstract

A latent class model for identifying classes of subjects in paired comparison choice experiments is developed. The model simultaneously estimates a probabilistic classification of subjects and the logit models' coefficients relating characteristics of objects to choices for each respective group among two alternatives in paired comparison experiments. A modest Monte Carlo analysis of algorithm performance is presented. The proposed model is illustrated with empirical data from a consumer psychology experiment that examines the determinants of perceived consumer risk. The predictive validity of the method is assessed and compared to that of several other procedures. The sensitivity of the method to (randomly) eliminate comparisons, which is important in view of reducing respondent fatigue in the task, is investigated.

Original languageEnglish (US)
Pages (from-to)1157-1170
Number of pages14
JournalDecision Sciences
Volume24
Issue number6
DOIs
StatePublished - Nov 1993

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Strategy and Management
  • Information Systems and Management
  • Management of Technology and Innovation

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