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Marginalized Transition Models and Likelihood Inference for Longitudinal Categorical Data

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  • Patrick J. Heagerty

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  • Patrick J. Heagerty, 2002. "Marginalized Transition Models and Likelihood Inference for Longitudinal Categorical Data," Biometrics, The International Biometric Society, vol. 58(2), pages 342-351, June.
    • Handle: RePEc:bla:biomet:v:58:y:2002:i:2:p:342-351
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2002.00342.x
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    Cited by:

    1. Jonathan S. Schildcrout & Patrick J. Heagerty, 2007. "Marginalized Models for Moderate to Long Series of Longitudinal Binary Response Data," Biometrics, The International Biometric Society, vol. 63(2), pages 322-331, June.
    2. Elsa Vazquez & Jeffrey R. Wilson, 2021. "Partitioned method of valid moment marginal model with Bayes interval estimates for correlated binary data with time-dependent covariates," Computational Statistics, Springer, vol. 36(4), pages 2701-2718, December.
    3. 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.
    4. Enrico A. Colosimo & Maria Arlene Fausto & Marta Afonso Freitas & Jorge Andrade Pinto, 2012. "Practical modeling strategies for unbalanced longitudinal data analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2005-2013, May.
    5. Lee, Keunbaik & Mercante, Donald, 2010. "Longitudinal nominal data analysis using marginalized models," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 208-218, January.
    6. Adriano Zanin Zambom & Seonjin Kim & Nancy Lopes Garcia, 2022. "Variable length Markov chain with exogenous covariates," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(2), pages 312-328, March.
    7. Molenberghs, Geert & Kenward, Michael G., 2010. "Semi-parametric marginal models for hierarchical data and their corresponding full models," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 585-597, February.
    8. Jonathan S. Schildcrout & Patrick J. Heagerty, 2011. "Outcome-Dependent Sampling from Existing Cohorts with Longitudinal Binary Response Data: Study Planning and Analysis," Biometrics, The International Biometric Society, vol. 67(4), pages 1583-1593, December.
    9. M. H. Goncalves & A. Azzalini, 2008. "Using Markov chains for marginal modelling of binary longitudinal data in an exact likelihood approach," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 157-181.
    10. Lee, Keunbaik & Sohn, Insuk & Kim, Donguk, 2016. "Analysis of long series of longitudinal ordinal data using marginalized models," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 363-371.
    11. Wenqin Pan & Donglin Zeng & Xihong Lin, 2009. "Estimation in Semiparametric Transition Measurement Error Models for Longitudinal Data," Biometrics, The International Biometric Society, vol. 65(3), pages 728-736, September.
    12. Jason Roy & Michael J. Daniels, 2008. "A General Class of Pattern Mixture Models for Nonignorable Dropout with Many Possible Dropout Times," Biometrics, The International Biometric Society, vol. 64(2), pages 538-545, June.
    13. Jonathan S. Schildcrout & Paul J. Rathouz, 2010. "Longitudinal Studies of Binary Response Data Following Case–Control and Stratified Case–Control Sampling: Design and Analysis," Biometrics, The International Biometric Society, vol. 66(2), pages 365-373, June.
    14. Gabriel Escarela & Luis Carlos Perez-Ruiz & Russell Bowater, 2009. "A copula-based Markov chain model for the analysis of binary longitudinal data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(6), pages 647-657.
    15. Lee, Keunbaik & Joo, Yongsung, 2019. "Marginalized models for longitudinal count data," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 47-58.
    16. M.J. Daniels & C. Wang & B.H. Marcus, 2014. "Fully Bayesian inference under ignorable missingness in the presence of auxiliary covariates," Biometrics, The International Biometric Society, vol. 70(1), pages 62-72, March.
    17. Gul Inan & Ozlem Ilk, 2019. "A marginalized multilevel model for bivariate longitudinal binary data," Statistical Papers, Springer, vol. 60(3), pages 601-628, June.
    18. Kenneth J. Wilkins & Garrett M. Fitzmaurice, 2006. "A Hybrid Model for Nonignorable Dropout in Longitudinal Binary Responses," Biometrics, The International Biometric Society, vol. 62(1), pages 168-176, March.
    19. Özgür Asar & Ozlem Ilk, 2016. "First-order marginalised transition random effects models with probit link function," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 925-942, April.
    20. A. N. Pettitt & T. T. Tran & M. A. Haynes & J. L. Hay, 2006. "A Bayesian hierarchical model for categorical longitudinal data from a social survey of immigrants," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(1), pages 97-114, January.
    21. Keunbaik Lee & Sanggil Kang & Xuefeng Liu & Daekwan Seo, 2011. "Likelihood-based approach for analysis of longitudinal nominal data using marginalized random effects models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(8), pages 1577-1590, July.

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