A model-based approach for visualizing the dimensional structure of ordered successive categories preference data

Wayne Desarbo, Joonwook Park, Crystal J. Scott

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

A cyclical conditional maximum likelihood estimation procedure is developed for the multidimensional unfolding of two- or three-way dominance data (e.g., preference, choice, consideration) measured on ordered successive category rating scales. The technical description of the proposed model and estimation procedure are discussed, as well as the rather unique joint spaces derived. We then conduct a modest Monte Carlo simulation to demonstrate the parameter recovery of the proposed methodology, as well as investigate the performance of various information heuristics for dimension selection. A consumer psychology application is provided where the spatial results of the proposed model are compared to solutions derived from various traditional multidimensional unfolding procedures. This application deals with consumers intending to buy new luxury sport-utility vehicles (SUVs). Finally, directions for future research are discussed.

Original languageEnglish (US)
Pages (from-to)1-20
Number of pages20
JournalPsychometrika
Volume73
Issue number1
DOIs
StatePublished - Mar 1 2008

Fingerprint

Model-based
Unfolding
Maximum likelihood estimation
Sports
Conditional Maximum Likelihood
Maximum Likelihood Estimation
Recovery
Monte Carlo Simulation
Joints
Heuristics
Psychology
Methodology
Model
Demonstrate
Monte Carlo simulation
Direction compound

All Science Journal Classification (ASJC) codes

  • Psychology(all)
  • Applied Mathematics

Cite this

Desarbo, Wayne ; Park, Joonwook ; Scott, Crystal J. / A model-based approach for visualizing the dimensional structure of ordered successive categories preference data. In: Psychometrika. 2008 ; Vol. 73, No. 1. pp. 1-20.
@article{bea8c1472e1d46e58003d3ed652995c6,
title = "A model-based approach for visualizing the dimensional structure of ordered successive categories preference data",
abstract = "A cyclical conditional maximum likelihood estimation procedure is developed for the multidimensional unfolding of two- or three-way dominance data (e.g., preference, choice, consideration) measured on ordered successive category rating scales. The technical description of the proposed model and estimation procedure are discussed, as well as the rather unique joint spaces derived. We then conduct a modest Monte Carlo simulation to demonstrate the parameter recovery of the proposed methodology, as well as investigate the performance of various information heuristics for dimension selection. A consumer psychology application is provided where the spatial results of the proposed model are compared to solutions derived from various traditional multidimensional unfolding procedures. This application deals with consumers intending to buy new luxury sport-utility vehicles (SUVs). Finally, directions for future research are discussed.",
author = "Wayne Desarbo and Joonwook Park and Scott, {Crystal J.}",
year = "2008",
month = "3",
day = "1",
doi = "10.1007/s11336-007-9015-2",
language = "English (US)",
volume = "73",
pages = "1--20",
journal = "Psychometrika",
issn = "0033-3123",
publisher = "Springer New York",
number = "1",

}

A model-based approach for visualizing the dimensional structure of ordered successive categories preference data. / Desarbo, Wayne; Park, Joonwook; Scott, Crystal J.

In: Psychometrika, Vol. 73, No. 1, 01.03.2008, p. 1-20.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A model-based approach for visualizing the dimensional structure of ordered successive categories preference data

AU - Desarbo, Wayne

AU - Park, Joonwook

AU - Scott, Crystal J.

PY - 2008/3/1

Y1 - 2008/3/1

N2 - A cyclical conditional maximum likelihood estimation procedure is developed for the multidimensional unfolding of two- or three-way dominance data (e.g., preference, choice, consideration) measured on ordered successive category rating scales. The technical description of the proposed model and estimation procedure are discussed, as well as the rather unique joint spaces derived. We then conduct a modest Monte Carlo simulation to demonstrate the parameter recovery of the proposed methodology, as well as investigate the performance of various information heuristics for dimension selection. A consumer psychology application is provided where the spatial results of the proposed model are compared to solutions derived from various traditional multidimensional unfolding procedures. This application deals with consumers intending to buy new luxury sport-utility vehicles (SUVs). Finally, directions for future research are discussed.

AB - A cyclical conditional maximum likelihood estimation procedure is developed for the multidimensional unfolding of two- or three-way dominance data (e.g., preference, choice, consideration) measured on ordered successive category rating scales. The technical description of the proposed model and estimation procedure are discussed, as well as the rather unique joint spaces derived. We then conduct a modest Monte Carlo simulation to demonstrate the parameter recovery of the proposed methodology, as well as investigate the performance of various information heuristics for dimension selection. A consumer psychology application is provided where the spatial results of the proposed model are compared to solutions derived from various traditional multidimensional unfolding procedures. This application deals with consumers intending to buy new luxury sport-utility vehicles (SUVs). Finally, directions for future research are discussed.

UR - http://www.scopus.com/inward/record.url?scp=41449085526&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=41449085526&partnerID=8YFLogxK

U2 - 10.1007/s11336-007-9015-2

DO - 10.1007/s11336-007-9015-2

M3 - Article

AN - SCOPUS:41449085526

VL - 73

SP - 1

EP - 20

JO - Psychometrika

JF - Psychometrika

SN - 0033-3123

IS - 1

ER -