Dummy covariates in CUB models
DOI:
https://doi.org/10.6092/issn.1973-2201/3529Abstract
In this paper we discuss the use of dummy variables as sensible covariates in a class of statistical models which aim at explaining the subjects’ preferences with respect to several items. After a brief introduction to CUB models, the work considers statistical interpretations of dummy covariates. Then, a simulation study is performed to evaluate the power discrimination of an asymptotic test among sub-populations. Some empirical evidences and concluding remarks end the paper.References
A. AGRESTI (2002), Categorical data analysis, 2nd edition, J. Wiley & Sons, New York.
R.D. BOCK, I. MOUSTAKI (2007), Item Response Theory in a General Framework, “Handbook of Statistics”, 26, North-Holland, Amsterdam, 469-513.
S. CAGNONE, A. GARDINI, S. MIGNANI (2004), New developments of latent variable models with ordinal data, Atti della XLII Riunione Scientifica SIS, Bari, vol. I, 1-12.
A. D’ELIA (2000a), Il meccanismo dei confronti appaiati nella modellistica per graduatorie: sviluppi statistici ed aspetti critici, “Quaderni di Statistica”, 2, 173-203.
A. D’ELIA (2003), A mixture models with covariates for ranks data: some inferential developments, “Quaderni di Statistica”, 5, 1-25.
A. D’ELIA, E. MAURIELLO, N. SITZIA (2001), Uno studio sulla scelta dei colori: esperienze e metodi statistici, Atti del Convegno nazionale su Matematica, Formazione Scientifica e Nuove Tecnologie, Montevarchi, 85-96.
A. D’ELIA, D. PICCOLO (2005a), A mixture model for preference data analysis, “Computational Statistics & Data Analysis”, 49, 917-934.
A. D’ELIA, D. PICCOLO (2005b), Uno studio sulla percezione delle emergenze metropolitane: un approccio modellistico, “Quaderni di Statistica”, 7, 121-161.
A. J. DOBSON (1990), An introduction to generalized linear models, Chapman & Hall, London.
M. IANNARIO (2009), A note on the identifiability of a mixture model for ordinal data, submitted.
M. IANNARIO (2007), A statistical approach for modelling Urban Audit Perception Surveys, “Quaderni di Statistica”, 9, 149-172.
M. IANNARIO, D. PICCOLO (2009), A new statistical model for the analysis of Customer Satisfaction, “Quality Technology and Quantitative Management”, forthcoming.
V. E. JOHNSON, J. H. ALBERT (1999), Ordinal data modeling, Springer, New York.
G. KING, M. TOMZ, J. WITTENBERG, (2000), Making the most of statistical analyses: improving interpretation and presentation, “American Journal of Political Science”, 44, 341-355.
C. J. LLOYD (1999), Statistical Analysis of categorical data, J. Wiley & Sons, New York.
J.I. MARDEN (1995), Analyzing and modelling rank data, Chapman & Hall, London.
P. MCCULLAGH (1980), Regression models for ordinal data (with discussion), “Journal of the Royal Statistical Society”, Series B, 42, 109-142.
P. MCCULLAGH, J. A. NELDER (1998), Generalized linear models, 2nd edition, Chapman & Hall, London.
I. MOUSTAKI (2000), A latent variable model for ordinal data, “Applied Psychological Measurement”, 24, 211-223.
I. MOUSTAKI (2003), A general class of latent variable model for ordinal manifest variables with covariate effects on the manifest and latent variables, “British Journal of Mathematical and Statistical Psychology”, 56, 337-357.
I. MOUSTAKI, M. KNOTT (2000), Generalized latent trait models, “Psychometrika”, 65, 391-411.
J. A. NELDER, R. W. M. WEDDERBURN (1972), Generalized linear models, “Journal of the Royal Statistical Society”, Series A, 135, 370-384.
D. PICCOLO (2003), On the moments of a mixture of uniform and shifted binomial random variables, “Quaderni di Statistica”, 5, 85-104.
D. PICCOLO (2006), Observed information matrix for MUB models, “Quaderni di Statistica”, 8, 33-78.
D. PICCOLO, A. D’ELIA (2008), A new approach for modelling consumers’ preferences, “Food and Quality Preference”, 19, 247-259.
D. PICCOLO, M. IANNARIO (2008), A package in R for CUB models inference, Version 1.1, available at http://www.dipstat.unina.it
D. A.POWER, Y. XIE (2000), Statistical methods for categorical data analysis, Academic Press, London.
J. S. SIMONOFF (2003), Analyzing categorical data, Springer, New York.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2008 Statistica
Copyrights and publishing rights of all the texts on this journal belong to the respective authors without restrictions.
This journal is licensed under a Creative Commons Attribution 4.0 International License (full legal code).
See also our Open Access Policy.
