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Conditional Second-Order Generalized Estimating Equations for Generalized Linear and Nonlinear Mixed-Effects Models

Author

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  • Vonesh E. F.
  • Wang H.
  • Nie L.
  • Majumdar D.

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Suggested Citation

  • Vonesh E. F. & Wang H. & Nie L. & Majumdar D., 2002. "Conditional Second-Order Generalized Estimating Equations for Generalized Linear and Nonlinear Mixed-Effects Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 271-283, March.
    • Handle: RePEc:bes:jnlasa:v:97:y:2002:m:march:p:271-283
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    Cited by:

    1. Kheradmandi, Ameneh & Rasekh, Abdolrahman, 2015. "Estimation in skew-normal linear mixed measurement error models," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 1-11.
    2. Li, Daniel H. & Wang, Liqun, 2016. "A weighted simulation-based estimator for incomplete longitudinal data models," Statistics & Probability Letters, Elsevier, vol. 113(C), pages 16-22.
    3. Stephen Toit & Robert Cudeck, 2009. "Estimation of the Nonlinear Random Coefficient Model when Some Random Effects Are Separable," Psychometrika, Springer;The Psychometric Society, vol. 74(1), pages 65-82, March.
    4. Kalyan Das & Angshuman Sarkar, 2014. "Robust inference for generalized partially linear mixed models that account for censored responses and missing covariates -- an application to Arctic data analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(11), pages 2418-2436, November.
    5. Geraci, Marco, 2019. "Modelling and estimation of nonlinear quantile regression with clustered data," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 30-46.
    6. Wu, Lang, 2007. "A computationally efficient method for nonlinear mixed-effects models with nonignorable missing data in time-varying covariates," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2410-2419, February.
    7. Liu, Wei & Wu, Lang, 2008. "A semiparametric nonlinear mixed-effects model with non-ignorable missing data and measurement errors for HIV viral data," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 112-122, September.
    8. Hongbin Zhang & Lang Wu, 2019. "An approximate method for generalized linear and nonlinear mixed effects models with a mechanistic nonlinear covariate measurement error model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(4), pages 471-499, May.
    9. Francis K. C. Hui & Samuel Müller & A. H. Welsh, 2017. "Joint Selection in Mixed Models using Regularized PQL," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1323-1333, July.
    10. Lee, Sik-Yum & Xu, Liang, 2004. "Influence analyses of nonlinear mixed-effects models," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 321-341, March.
    11. Mengfei Ran & Yihe Yang, 2022. "Optimal Estimation of Large Functional and Longitudinal Data by Using Functional Linear Mixed Model," Mathematics, MDPI, vol. 10(22), pages 1-28, November.
    12. Zhi Tang & Yang Yu, 2023. "American Economic Stakeholder Sentiments towards Chinese Firms’ Innovation Capability: The Role of State Political Environment and Firm Ownership," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    13. Karim Zare & Abdolrahman Rasekh & Ali Rasekhi, 2012. "Estimation of variance components in linear mixed measurement error models," Statistical Papers, Springer, vol. 53(4), pages 849-863, November.
    14. Cui, Hengjian & Ng, Kai W. & Zhu, Lixing, 2004. "Estimation in mixed effects model with errors in variables," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 53-73, October.
    15. Kunling Wu & Lang Wu, 2007. "Generalized linear mixed models with informative dropouts and missing covariates," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 66(1), pages 1-18, July.

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