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Marginalized Models for Moderate to Long Series of Longitudinal Binary Response Data

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  • Jonathan S. Schildcrout
  • Patrick J. Heagerty

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  • 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.
    • Handle: RePEc:bla:biomet:v:63:y:2007:i:2:p:322-331
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2006.00680.x
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    References listed on IDEAS

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    1. Zengri Wang, 2003. "Matching conditional and marginal shapes in binary random intercept models using a bridge distribution function," Biometrika, Biometrika Trust, vol. 90(4), pages 765-775, December.
    2. Diana Miglioretti & Patrick Heagerty, 2004. "Marginal Modeling of Multilevel Binary Data with Time-Varying Covariates," UW Biostatistics Working Paper Series 1050, Berkeley Electronic Press.
    3. Brenda Kurland & Patrick Heagerty, 2004. "Marginalized Transition Models for Longitudinal Binary Data With Ignorable and Nonignorable Dropout," UW Biostatistics Working Paper Series 1054, Berkeley Electronic Press.
    4. 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.
    5. Patrick J. Heagerty, 1999. "Marginally Specified Logistic-Normal Models for Longitudinal Binary Data," Biometrics, The International Biometric Society, vol. 55(3), pages 688-698, September.
    6. Patrick J. Heagerty & Scott L. Zeger, 2000. "Multivariate Continuation Ratio Models: Connections and Caveats," Biometrics, The International Biometric Society, vol. 56(3), pages 719-732, September.
    7. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
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    Cited by:

    1. Loni Philip Tabb & Eric J. Tchetgen Tchetgen & Greg A. Wellenius & Brent A. Coull, 2016. "Marginalized Zero-Altered Models for Longitudinal Count Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(2), pages 181-203, October.
    2. 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.
    3. 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.
    4. Peter McCullagh, 2008. "Sampling bias and logistic models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 643-677, September.
    5. Lee, Keunbaik & Joo, Yongsung, 2019. "Marginalized models for longitudinal count data," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 47-58.
    6. 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.

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