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The analysis of ordered categorical data: An overview and a survey of recent developments

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  • Ivy Liu
  • Alan Agresti

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Suggested Citation

  • Ivy Liu & Alan Agresti, 2005. "The analysis of ordered categorical data: An overview and a survey of recent developments," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(1), pages 1-73, June.
  • Handle: RePEc:spr:testjl:v:14:y:2005:i:1:p:1-73
    DOI: 10.1007/BF02595397
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    References listed on IDEAS

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    1. A. Fielding, 1999. "Why use arbitrary points scores?: ordered categories in models of educational progress," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(3), pages 303-328.
    2. 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.
    3. Agresti, Alan & Chuang, Christy, 1989. "Model-based Bayesian methods for estimating cell proportions in cross-classification tables having ordered categories," Computational Statistics & Data Analysis, Elsevier, vol. 7(3), pages 245-258, February.
    4. Bartolucci F. & Forcina A., 2002. "Extended RC Association Models Allowing for Order Restrictions and Marginal Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1192-1199, December.
    5. Tutz, Gerhard & Hennevogl, Wolfgang, 1996. "Random effects in ordinal regression models," Computational Statistics & Data Analysis, Elsevier, vol. 22(5), pages 537-557, September.
    6. J. G. Booth & J. P. Hobert, 1999. "Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 265-285.
    7. Agresti, Alan & Coull, Brent A., 1998. "Order-restricted inference for monotone trend alternatives in contingency tables," Computational Statistics & Data Analysis, Elsevier, vol. 28(2), pages 139-155, August.
    8. Kim, Donguk & Agresti, Alan, 1997. "Nearly exact tests of conditional independence and marginal homogeneity for sparse contingency tables," Computational Statistics & Data Analysis, Elsevier, vol. 24(1), pages 89-104, March.
    9. Simonoff, Jeffrey S., 1987. "Probability estimation via smoothing in sparse contingency tables with ordered categories," Statistics & Probability Letters, Elsevier, vol. 5(1), pages 55-63, January.
    10. Agresti, Alan & Yang, Ming-Chung, 1987. "An empirical investigation of some effects of sparseness in contingency tables," Computational Statistics & Data Analysis, Elsevier, vol. 5(1), pages 9-21.
    11. Bartolucci, F. & Scaccia, L., 2004. "Testing for positive association in contingency tables with fixed margins," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 195-210, August.
    12. Brunner, Edgar & Munzel, Ulrich & Puri, Madan L., 1999. "Rank-Score Tests in Factorial Designs with Repeated Measures," Journal of Multivariate Analysis, Elsevier, vol. 70(2), pages 286-317, August.
    13. Tutz, Gerhard, 1991. "Sequential models in categorical regression," Computational Statistics & Data Analysis, Elsevier, vol. 11(3), pages 275-295, May.
    14. Samuel M. Mwalili & Emmanuel Lesaffre & Dominique Declerck, 2005. "A Bayesian ordinal logistic regression model to correct for interobserver measurement error in a geographical oral health study," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(1), pages 77-93.
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    Citations

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    Cited by:

    1. Fernández, D. & Arnold, R. & Pledger, S., 2016. "Mixture-based clustering for the ordered stereotype model," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 46-75.
    2. Eleni Matechou & Ivy Liu & Daniel Fernández & Miguel Farias & Bergljot Gjelsvik, 2016. "Biclustering Models for Two-Mode Ordinal Data," Psychometrika, Springer;The Psychometric Society, vol. 81(3), pages 611-624, September.
    3. Li, Yonghai & Schafer, Daniel W., 2008. "Likelihood analysis of the multivariate ordinal probit regression model for repeated ordinal responses," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3474-3492, March.
    4. Bhat, Chandra R. & Astroza, Sebastian & Hamdi, Amin S., 2017. "A spatial generalized ordered-response model with skew normal kernel error terms with an application to bicycling frequency," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 126-148.
    5. repec:ipf:psejou:v:41:y:2017:i:1:p:85-108 is not listed on IDEAS
    6. repec:eee:jfinec:v:125:y:2017:i:3:p:561-588 is not listed on IDEAS
    7. Fuks, Mauricio & Salazar, Esther, 2008. "Applying models for ordinal logistic regression to the analysis of household electricity consumption classes in Rio de Janeiro, Brazil," Energy Economics, Elsevier, vol. 30(4), pages 1672-1692, July.
    8. repec:gam:jrisks:v:6:y:2018:i:2:p:57-:d:147107 is not listed on IDEAS
    9. Pardo, L. & Pardo, M.C., 2008. "An extension of likelihood-ratio-test for testing linear hypotheses in the baseline-category logit model," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1477-1489, January.
    10. Nooraee, Nazanin & Molenberghs, Geert & van den Heuvel, Edwin R., 2014. "GEE for longitudinal ordinal data: Comparing R-geepack, R-multgee, R-repolr, SAS-GENMOD, SPSS-GENLIN," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 70-83.
    11. 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.
    12. Celine Marielle Laffont & Marc Vandemeulebroecke & Didier Concordet, 2014. "Multivariate Analysis of Longitudinal Ordinal Data With Mixed Effects Models, With Application to Clinical Outcomes in Osteoarthritis," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 955-966, September.
    13. M. Pardo, 2011. "Testing equality restrictions in generalized linear models for multinomial data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(2), pages 231-253, March.
    14. Keunbaik Lee & Michael J. Daniels, 2007. "A Class of Markov Models for Longitudinal Ordinal Data," Biometrics, The International Biometric Society, vol. 63(4), pages 1060-1067, December.
    15. Bartoll, Xavier & Gil, Joan & Ramos, Raul, 2018. "Has the Economic Crisis Worsened the Work-Related Stress and Mental Health of Temporary Workers in Spain?," IZA Discussion Papers 11701, Institute for the Study of Labor (IZA).
    16. M. Menéndez & L. Pardo & M. Pardo, 2009. "Preliminary phi-divergence test estimators for linear restrictions in a logistic regression model," Statistical Papers, Springer, vol. 50(2), pages 277-300, March.
    17. Xavier Bartoll & Joan Gil & Raul Ramos, 2018. "“Has the economic crisis worsened the work-related stress and mental health of temporary workers in Spain?”," IREA Working Papers 201819, University of Barcelona, Research Institute of Applied Economics, revised Sep 2018.

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