Generalized Latent Class Analysis: A New Methodology for Market Structure Analysis

Published 1 January 1989

Ingo Böckenholt, Wolfgang Gaul

Citations11

TL;DR

A generalization of LCA (Latent Class Analysis) is presented which allows a simultaneous classification and MDS (MultiDimensional Scaling) of ordered categorical data and allows a graphical representation of the classification results obtained.

Abstract

In this paper a generalization of LCA (Latent Class Analysis) is presented which allows a simultaneous classification and MDS (MultiDimensional Scaling) of ordered categorical data. This approach is managerially useful in several ways, because additional background variables can be directly incorporated to identify latent class specific response probabilities. Furthermore, this technique allows a graphical representation of the classification results obtained. Essential features of the methodology will be demonstrated in the empirical part of this paper.

Keywords

Decision SciencesBusiness, Management and Accounting

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