A Hierarchical Bayesian Procedure for Two-Mode Cluster Analysis

Psychometrika, Volume 69, Issue 4, pp 547-572, 2004

Posted: 11 Jun 2016

See all articles by Wayne S. DeSarbo

Wayne S. DeSarbo

Pennsylvania State University

Duncan K. H. Fong

Pennsylvania State University

John Liechty

Pennsylvania State University, University Park

M. Kim Saxton

Indiana University - Kelley School of Business - Department of Marketing

Date Written: December 2004

Abstract

This manuscript introduces a new Bayesian finite mixture methodology for the joint clustering of row and column stimuli/objects associated with two-mode asymmetric proximity, dominance, or profile data. That is, common clusters are derived which partition both the row and column stimuli/objects simultaneously into the same derived set of clusters. In this manner, interrelationships between both sets of entities (rows and columns) are easily ascertained. We describe the technical details of the proposed two-mode clustering methodology including its Bayesian mixture formulation and a Bayes factor heuristic for model selection. We present a modest Monte Carlo analysis to investigate the performance of the proposed Bayesian two-mode clustering procedure with respect to synthetically created data whose structure and parameters are known. Next, a consumer psychology application is provided examining physician pharmaceutical prescription behavior for various brands of prescription drugs in the neuroscience health market. We conclude by discussing several fertile areas for future research.

Keywords: Cluster analysis, hierarchical Bayesian analysis, finite mixture models, consumer psychology

Suggested Citation

DeSarbo, Wayne S. and Fong, Duncan K. H. and Liechty, John and Saxton, M. Kim, A Hierarchical Bayesian Procedure for Two-Mode Cluster Analysis (December 2004). Psychometrika, Volume 69, Issue 4, pp 547-572, 2004, Available at SSRN: https://ssrn.com/abstract=2793172

Wayne S. DeSarbo (Contact Author)

Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

Duncan K. H. Fong

Pennsylvania State University ( email )

308 armsby
university park, PA 16802
United States

John Liechty

Pennsylvania State University, University Park ( email )

University Park
State College, PA 16802
United States

M. Kim Saxton

Indiana University - Kelley School of Business - Department of Marketing ( email )

Kelley School of Business
Bloomington, IN 47405
United States

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