A Latent Class Procedure for the Structural Analysis of Two-Way Compositional Data

Journal of Classification, Volume 10, Issue 2, pp 159-193 (1993)

35 Pages Posted: 4 Jun 2016

See all articles by Wayne S. DeSarbo

Wayne S. DeSarbo

Pennsylvania State University

Venkatram Ramaswamy

University of Michigan, Stephen M. Ross School of Business

Peter Lenk

University of Michigan, Stephen M. Ross School of Business

Date Written: December 1993

Abstract

This paper develops a new procedure for simultaneously performing multidimensional scaling and cluster analysis on two-way compositional data of proportions. The objective of the proposed procedure is to delineate patterns of variability in compositions across subjects by simultaneously clustering subjects into latent classes or groups and estimating a joint space of stimulus coordinates and class-specific vectors in a multidimensional space. We use a conditional mixture, maximum likelihood framework with an E-M algorithm for parameter estimation. The proposed procedure is illustrated using a compositional data set reflecting proportions of viewing time across television networks for an area sample of households.

Keywords: Compositional data, Finite mixture distributions, Cluster analysis, Multidimensional scaling, E-M algorithm, Latent class analysis

Suggested Citation

DeSarbo, Wayne S. and Ramaswamy, Venkatram and Lenk, Peter, A Latent Class Procedure for the Structural Analysis of Two-Way Compositional Data (December 1993). Journal of Classification, Volume 10, Issue 2, pp 159-193 (1993), Available at SSRN: https://ssrn.com/abstract=2789032

Wayne S. DeSarbo (Contact Author)

Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

Venkatram Ramaswamy

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan Street
Ann Arbor, MI MI 48109-1234
United States
734-763-5932 (Phone)
734-936-0279 (Fax)

Peter Lenk

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan Street
Ann Arbor, MI MI 48109
United States

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