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The Goodness of Fit of Latent Trait Models in Attitude Measurement

Author

Listed:
  • DAVID J. BARTHOLOMEW

    (London School of Economics and Political Science)

  • PANAGIOTA TZAMOURANI

    (London School of Economics and Political Science)

Abstract

The logit latent trait model offers a promising means of constructing attitude scales in sociology. The adequacy of such scales depends on the appropriateness of the model on which they are based. This article shows that the standard goodness-of-fit tests, based on chi-square distributions, are often invalid. It proposes an alternative approach based on Monte Carlo methods and residuals that has the additional merit of showing how the set of items may be refined to improve the fit and hence the quality of the scale.

Suggested Citation

  • David J. Bartholomew & Panagiota Tzamourani, 1999. "The Goodness of Fit of Latent Trait Models in Attitude Measurement," Sociological Methods & Research, , vol. 27(4), pages 525-546, May.
    • Handle: RePEc:sae:somere:v:27:y:1999:i:4:p:525-546
    DOI: 10.1177/0049124199027004003
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    Cited by:

    1. Isabella Morlini, 2012. "A latent variables approach for clustering mixed binary and continuous variables within a Gaussian mixture model," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(1), pages 5-28, April.
    2. Alberto Maydeu-Olivares & Rosa Montaño, 2013. "How Should We Assess the Fit of Rasch-Type Models? Approximating the Power of Goodness-of-Fit Statistics in Categorical Data Analysis," Psychometrika, Springer;The Psychometric Society, vol. 78(1), pages 116-133, January.
    3. Carolina Navarro & Luis Ayala & José Labeaga, 2010. "Housing deprivation and health status: evidence from Spain," Empirical Economics, Springer, vol. 38(3), pages 555-582, June.
    4. Yuqi Gu & Jingchen Liu & Gongjun Xu & Zhiliang Ying, 2018. "Hypothesis Testing of the Q-matrix," Psychometrika, Springer;The Psychometric Society, vol. 83(3), pages 515-537, September.
    5. Shing-On Leung, 2008. "A Three-Dimensional Latent Variable Model for Attitude Scales," Sociological Methods & Research, , vol. 37(1), pages 135-154, August.
    6. Juan Manuel Pérez-Salamero González & Marta Regúlez-Castillo & Manuel Ventura-Marco & Carlos Vidal-Meliá, 2017. "Automatic regrouping of strata in the chi-square test," Documentos de Trabajo del ICAE 2017-24, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    7. Li Cai, 2010. "A Two-Tier Full-Information Item Factor Analysis Model with Applications," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 581-612, December.
    8. Taha Hannachi & Sonya Yakimova & Alain Somat, 2024. "A Follow up on the Continuum Theory of Eco-Anxiety: Analysis of the Climate Change Anxiety Scale Using Item Response Theory among French Speaking Population," IJERPH, MDPI, vol. 21(9), pages 1-16, August.
    9. Albert Maydeu-Olivares & Harry Joe, 2006. "Limited Information Goodness-of-fit Testing in Multidimensional Contingency Tables," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 713-732, December.
    10. Moustaki, Irini & Papageorgiou, Ioulia, 2005. "Latent class models for mixed variables with applications in Archaeometry," Computational Statistics & Data Analysis, Elsevier, vol. 48(3), pages 659-675, March.
    11. Silvia cagnone & Stefania Mignani, 2007. "Assessing the goodness of fit of a latent variable model for ordinal data," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 337-361.

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