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On the use of heterogeneous thresholds ordinal regression models to account for individual differences in response style

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  • Timothy Johnson

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  • Timothy Johnson, 2003. "On the use of heterogeneous thresholds ordinal regression models to account for individual differences in response style," Psychometrika, Springer;The Psychometric Society, vol. 68(4), pages 563-583, December.
    • Handle: RePEc:spr:psycho:v:68:y:2003:i:4:p:563-583
    DOI: 10.1007/BF02295612
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    References listed on IDEAS

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    1. Rossi P. E & Gilula Z. & Allenby G. M, 2001. "Overcoming Scale Usage Heterogeneity: A Bayesian Hierarchical Approach," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 20-31, March.
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    Cited by:

    1. Anne Thissen-Roe & David Thissen, 2013. "A Two-Decision Model for Responses to Likert-Type Items," Journal of Educational and Behavioral Statistics, , vol. 38(5), pages 522-547, October.
    2. Jay Verkuilen & Michael Smithson, 2012. "Mixed and Mixture Regression Models for Continuous Bounded Responses Using the Beta Distribution," Journal of Educational and Behavioral Statistics, , vol. 37(1), pages 82-113, February.
    3. de Jong, M.G., 2006. "Response bias in international marketing research," Other publications TiSEM 5d4031be-97b5-4db3-962b-2, Tilburg University, School of Economics and Management.
    4. Gerhard Tutz, 2021. "Hierarchical Models for the Analysis of Likert Scales in Regression and Item Response Analysis," International Statistical Review, International Statistical Institute, vol. 89(1), pages 18-35, April.
    5. Nino Hardt & Alex Varbanov & Greg M. Allenby, 2016. "Monetizing Ratings Data for Product Research," Marketing Science, INFORMS, vol. 35(5), pages 713-726, September.
    6. Gerhard Tutz, 2020. "Modelling heterogeneity: on the problem of group comparisons with logistic regression and the potential of the heterogeneous choice 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. 14(3), pages 517-542, September.
    7. Bettina Grün & Sara Dolnicar, 2016. "Response style corrected market segmentation for ordinal data," Marketing Letters, Springer, vol. 27(4), pages 729-741, December.
    8. Roberto Colombi & Sabrina Giordano & Gerhard Tutz, 2021. "A Rating Scale Mixture Model to Account for the Tendency to Middle and Extreme Categories," Journal of Educational and Behavioral Statistics, , vol. 46(6), pages 682-716, December.
    9. Martijn Jong & Jan-Benedict Steenkamp, 2010. "Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research," Psychometrika, Springer;The Psychometric Society, vol. 75(1), pages 3-32, March.
    10. Dirk Lubbe & Christof Schuster, 2020. "A Scaled Threshold Model for Measuring Extreme Response Style," Journal of Educational and Behavioral Statistics, , vol. 45(1), pages 86-107, February.
    11. Timothy R. Johnson & Daniel M. Bolt, 2010. "On the Use of Factor-Analytic Multinomial Logit Item Response Models to Account for Individual Differences in Response Style," Journal of Educational and Behavioral Statistics, , vol. 35(1), pages 92-114, February.
    12. Timothy Johnson, 2007. "Discrete Choice Models for Ordinal Response Variables: A Generalization of the Stereotype Model," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 489-504, December.
    13. Rosaria Simone & Gerhard Tutz, 2018. "Modelling uncertainty and response styles in ordinal data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 224-245, August.
    14. Kim, Jung Seek & Ratchford, Brian T., 2013. "A Bayesian multivariate probit for ordinal data with semiparametric random-effects," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 192-208.
    15. Omori, Yasuhiro & Miyawaki, Koji, 2010. "Tobit model with covariate dependent thresholds," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2736-2752, November.
    16. Fang Liu & Xiaojing Wang & Roeland Hancock & Ming-Hui Chen, 2022. "Bayesian Model Assessment for Jointly Modeling Multidimensional Response Data with Application to Computerized Testing," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1290-1317, December.
    17. Pieter Schoonees & Michel Velden & Patrick Groenen, 2015. "Constrained Dual Scaling for Detecting Response Styles in Categorical Data," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 968-994, December.
    18. Gerhard Tutz & Moritz Berger, 2016. "Response Styles in Rating Scales," Journal of Educational and Behavioral Statistics, , vol. 41(3), pages 239-268, June.
    19. Lynd Bacon & Peter Lenk, 2012. "Augmenting discrete-choice data to identify common preference scales for inter-subject analyses," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 453-474, December.

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