A Latent Class Probit Model for Analyzing Pick Any/N Data

Journal of Classification, Volume 8, Issue 1, pp 45-63

19 Pages Posted: 1 Jun 2016

See all articles by Geert De Soete

Geert De Soete

Ghent University

Wayne S. DeSarbo

Pennsylvania State University

Date Written: January 1991

Abstract

A latent class probit model is developed in which it is assumed that the binary data of a particular subject follow a finite mixture of multivariate Bermoulli distributions. An EM algorithm for fitting the model is described and a Monte Carlo procedure for testing the number of latent classes that is required for adequately describing the data is discussed. In the final section, an application of the latent class probit model to some intended purchase data for residential telecommunication devices is reported.

Keywords: Probit Model, Latent Class Analysis, Finite Mixture Distribution, EM Algorithm, Monte Carlo Significance Test, Market Segmentation

Suggested Citation

De Soete, Geert and DeSarbo, Wayne S., A Latent Class Probit Model for Analyzing Pick Any/N Data (January 1991). Journal of Classification, Volume 8, Issue 1, pp 45-63, Available at SSRN: https://ssrn.com/abstract=2787346

Geert De Soete

Ghent University ( email )

Coupure Links 653
Gent, 9000
Belgium

Wayne S. DeSarbo (Contact Author)

Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

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