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

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  1. 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.
  2. Maynou, Laia & Cairns, John, 2018. "What is driving HTA decision-making? Evidence from cancer drug reimbursement decisions from 6 European countries," LSE Research Online Documents on Economics 90877, London School of Economics and Political Science, LSE Library.
  3. Sime Smolic, 2017. "The determinants of health among the population aged 50 and over: evidence from Croatia," Public Sector Economics, Institute of Public Finance, vol. 41(1), pages 85-108.
  4. Baruch, Shmuel & Panayides, Marios & Venkataraman, Kumar, 2017. "Informed trading and price discovery before corporate events," Journal of Financial Economics, Elsevier, vol. 125(3), pages 561-588.
  5. Högberg, Hans & Svensson, Elisabeth, 2008. "An Overview of Methods in the Analysis of Dependent ordered catagorical Data: Assumptions and Implications," Working Papers 2008:7, Örebro University, School of Business.
  6. Tatjana Miljkovic & Daniel Fernández, 2018. "On Two Mixture-Based Clustering Approaches Used in Modeling an Insurance Portfolio," Risks, MDPI, vol. 6(2), pages 1-18, May.
  7. Kędra, Arleta & Maleszyk, Piotr & Visvizi, Anna, 2023. "Engaging citizens in land use policy in the smart city context," Land Use Policy, Elsevier, vol. 129(C).
  8. Elena Castilla & Nirian Martín & Leandro Pardo, 2018. "Minimum phi-divergence estimators for multinomial logistic regression with complex sample design," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(3), pages 381-411, July.
  9. Corduas, Marcella, 2015. "A statistical model for consumer preferences: the case of Italian extra virgin olive oil," 143rd Joint EAAE/AAEA Seminar, March 25-27, 2015, Naples, Italy 202701, European Association of Agricultural Economists.
  10. repec:jss:jstsof:32:i10 is not listed on IDEAS
  11. Varin, Cristiano & Vidoni, Paolo, 2006. "Pairwise likelihood inference for ordinal categorical time series," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2365-2373, December.
  12. A.Y. Kombo & H. Mwambi & G. Molenberghs, 2017. "Multiple imputation for ordinal longitudinal data with monotone missing data patterns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(2), pages 270-287, January.
  13. Maynou, Laia & Cairns, John, 2019. "What is driving HTA decision-making? Evidence from cancer drug reimbursement decisions from 6 European countries," Health Policy, Elsevier, vol. 123(2), pages 130-139.
  14. 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.
  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 of Labor Economics (IZA).
  16. Bambio, Yiriyibin & Bouayad Agha, Salima, 2018. "Land tenure security and investment: Does strength of land right really matter in rural Burkina Faso?," World Development, Elsevier, vol. 111(C), pages 130-147.
  17. Wei, Zheng & Kim, Daeyoung, 2021. "On exploratory analytic method for multi-way contingency tables with an ordinal response variable and categorical explanatory variables," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
  18. Ivy Liu & Daniel Fernández, 2020. "Discussion on “Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer‐Lemeshow test” by Giovanni Nattino, Michael L. Pennell, and Stanley Lemeshow," Biometrics, The International Biometric Society, vol. 76(2), pages 564-568, June.
  19. 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.
  20. 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.
  21. 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.
  22. Jan Gertheiss & Gerhard Tutz, 2009. "Penalized Regression with Ordinal Predictors," International Statistical Review, International Statistical Institute, vol. 77(3), pages 345-365, December.
  23. Liu, Dungang & Li, Shaobo & Yu, Yan & Moustaki, Irini, 2020. "Assessing partial association between ordinal variables: quantification, visualization, and hypothesis testing," LSE Research Online Documents on Economics 105558, London School of Economics and Political Science, LSE Library.
  24. Meltem Ucal & Simge Günay, 2022. "Household Happiness and Fuel Poverty: a Cross-Sectional Analysis on Turkey," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 17(1), pages 391-420, February.
  25. Chi Tim Ng & Johan Lim & Kyu S. Hahn, 2011. "Testing stochastic orders in tails of contingency tables," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(6), pages 1133-1149, March.
  26. 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.
  27. 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.
  28. 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.
  29. Roy Costilla & Ivy Liu & Richard Arnold & Daniel Fernández, 2019. "Bayesian model-based clustering for longitudinal ordinal data," Computational Statistics, Springer, vol. 34(3), pages 1015-1038, September.
  30. Daniel Fernández & Louise McMillan & Richard Arnold & Martin Spiess & Ivy Liu, 2022. "Goodness-of-Fit and Generalized Estimating Equation Methods for Ordinal Responses Based on the Stereotype Model," Stats, MDPI, vol. 5(2), pages 1-14, June.
  31. Rasheed A. Adeyemi & Temesgen Zewotir & Shaun Ramroop, 2016. "Semiparametric Multinomial Ordinal Model to Analyze Spatial Patterns of Child Birth Weight in Nigeria," IJERPH, MDPI, vol. 13(11), pages 1-22, November.
  32. Högberg, Hans & Svensson, Elisabeth, 2008. "Comparison of methods in the analysis of dependent ordered catagorical data," Working Papers 2008:6, Örebro University, School of Business.
  33. Gerhard Tutz & Micha Schneider & Maria Iannario & Domenico Piccolo, 2017. "Mixture models for ordinal responses to account for uncertainty of choice," 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. 11(2), pages 281-305, June.
  34. Wei, Zheng & Wang, Li & Liao, Shu-Min & Kim, Daeyoung, 2023. "On the exploration of regression dependence structures in multidimensional contingency tables with ordinal response variables," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
  35. Chapman, Andrew & Shigetomi, Yosuke & Karmaker, Shamal Chandra & Saha, Bidyut & Brooks, Caleb, 2022. "Cultural and demographic energy system awareness and preference: Implications for future energy system design in the United States," Energy Economics, Elsevier, vol. 112(C).
  36. 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.
  37. Tutz, G. & Berger, M., 2017. "Separating location and dispersion in ordinal regression models," Econometrics and Statistics, Elsevier, vol. 2(C), pages 131-148.
  38. 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.
  39. 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.
  40. Alessandro Barbiero, 2021. "Inducing a desired value of correlation between two point-scale variables: a two-step procedure using copulas," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(2), pages 307-334, June.
  41. Esteban Sánchez-Moreno & Lorena Gallardo-Peralta, 2021. "From Income Inequalities to Social Exclusion: The Impact of the Great Recession on Self-Rated Health in Spain During the Onset of the Economic Crisis," SAGE Open, , vol. 11(4), pages 21582440211, October.
  42. 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.
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