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GEE for Multinomial Responses Using a Local Odds Ratios Parameterization

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  • Anestis Touloumis
  • Alan Agresti
  • Maria Kateri

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  • Anestis Touloumis & Alan Agresti & Maria Kateri, 2013. "GEE for Multinomial Responses Using a Local Odds Ratios Parameterization," Biometrics, The International Biometric Society, vol. 69(3), pages 633-640, September.
    • Handle: RePEc:bla:biomet:v:69:y:2013:i:3:p:633-640
    DOI: 10.1111/biom.12054
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    1. N. Rao Chaganty & Harry Joe, 2006. "Range of correlation matrices for dependent Bernoulli random variables," Biometrika, Biometrika Trust, vol. 93(1), pages 197-206, March.
    2. N. Rao Chaganty & Harry Joe, 2004. "Efficiency of generalized estimating equations for binary responses," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(4), pages 851-860, November.
    3. Becker, Mark P., 1989. "On the bivariate normal distribution and association models for ordinal categorical data," Statistics & Probability Letters, Elsevier, vol. 8(5), pages 435-440, October.
    4. You-Gan Wang, 2003. "Working correlation structure misspecification, estimation and covariate design: Implications for generalised estimating equations performance," Biometrika, Biometrika Trust, vol. 90(1), pages 29-41, March.
    5. N. R. Parsons & R. N. Edmondson & S. G. Gilmour, 2006. "A generalized estimating equation method for fitting autocorrelated ordinal score data with an application in horticultural research," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(4), pages 507-524, August.
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    Cited by:

    1. 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.
    2. Alan Agresti, 2014. "Two Bayesian/frequentist challenges for categorical data analyses," METRON, Springer;Sapienza Università di Roma, vol. 72(2), pages 125-132, August.
    3. Yuqi Tian & Bryan E. Shepherd & Chun Li & Donglin Zeng & Jonathan S. Schildcrout, 2023. "Analyzing clustered continuous response variables with ordinal regression models," Biometrics, The International Biometric Society, vol. 79(4), pages 3764-3777, December.
    4. Dale Bowman & E. Olusegun George, 2017. "Weighted least squares estimation for exchangeable binary data," Computational Statistics, Springer, vol. 32(4), pages 1747-1765, December.
    5. J. Perin & J. S. Preisser & C. Phillips & B. Qaqish, 2014. "Regression analysis of correlated ordinal data using orthogonalized residuals," Biometrics, The International Biometric Society, vol. 70(4), pages 902-909, December.
    6. Carlos Alberto GÓMEZ SILVA, 2014. "Clasificación de colegios según las Pruebas SABER 11 del ICFES en el Período 2001-2011: un Análisis Longitudinal a Través del Uso de Modelos Marginales (MM)," Archivos de Economía 12314, Departamento Nacional de Planeación.
    7. Alan Agresti & Maria Kateri, 2019. "The class of CUB models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 445-449, September.
    8. Gómez Silva Carlos Alberto, 2016. "Clasificación de colegios según las pruebas Saber 11 del ICFES: un análisis usando modelos marginales (MM)," Revista Sociedad y Economía, Universidad del Valle, CIDSE, vol. 0(30), pages 11-404, January.
    9. 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.
    10. Ronald Herrera & Ursula Berger & Jon Genuneit & Jessica Gerlich & Dennis Nowak & Wolff Schlotz & Christian Vogelberg & Erika Von Mutius & Gudrun Weinmayr & Doris Windstetter & Matthias Weigl & Katja R, 2017. "Chronic Stress in Young German Adults: Who Is Affected? A Prospective Cohort Study," IJERPH, MDPI, vol. 14(11), pages 1-13, October.
    11. Gem Stapleton & Peter Chapman & Peter Rodgers & Anestis Touloumis & Andrew Blake & Aidan Delaney, 2019. "The efficacy of Euler diagrams and linear diagrams for visualizing set cardinality using proportions and numbers," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-25, March.
    12. Thomas, Robert D. & Davis, John W. & Cuccaro, Paula M. & Gemeinhardt, Gretchen L., 2022. "Assessing associations between insecure income and US workers’ health: An IPUMS-MEPS analysis," Social Science & Medicine, Elsevier, vol. 309(C).

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