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Exact and Approximate Inferences for Nonlinear Mixed-Effects Models With Missing Covariates

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  • Lang Wu

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  • Lang Wu, 2004. "Exact and Approximate Inferences for Nonlinear Mixed-Effects Models With Missing Covariates," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 700-709, January.
    • Handle: RePEc:bes:jnlasa:v:99:y:2004:p:700-709
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    Cited by:

    1. 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.
    2. Christopher R. Bollinger & Barry T. Hirsch, 2006. "Match Bias from Earnings Imputation in the Current Population Survey: The Case of Imperfect Matching," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 483-520, July.
    3. Noh, Maengseok & Wu, Lang & Lee, Youngjo, 2012. "Hierarchical likelihood methods for nonlinear and generalized linear mixed models with missing data and measurement errors in covariates," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 42-51.
    4. Elson Tomás & Susana Vinga & Alexandra M. Carvalho, 2017. "Unsupervised learning of pharmacokinetic responses," Computational Statistics, Springer, vol. 32(2), pages 409-428, June.
    5. Liang, Hua, 2008. "Generalized partially linear models with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 880-895, May.
    6. Liang, Hua & Su, Haiyan & Zou, Guohua, 2008. "Confidence intervals for a common mean with missing data with applications in an AIDS study," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 546-553, December.
    7. Wu, Lang, 2008. "An approximate method for nonlinear mixed-effects models with nonignorably missing covariates," Statistics & Probability Letters, Elsevier, vol. 78(4), pages 384-389, March.
    8. Marc Lavielle & Adeline Samson & Ana Karina Fermin & France Mentré, 2011. "Maximum Likelihood Estimation of Long-Term HIV Dynamic Models and Antiviral Response," Biometrics, The International Biometric Society, vol. 67(1), pages 250-259, March.
    9. Samson, Adeline & Lavielle, Marc & Mentre, France, 2006. "Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1562-1574, December.
    10. Fu, Liyong & Wang, Mingliang & Lei, Yuancai & Tang, Shouzheng, 2014. "Parameter estimation of two-level nonlinear mixed effects models using first order conditional linearization and the EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 173-183.

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