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An Estimation Method for the Semiparametric Mixed Effects Model

Author

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  • Huageng Tao
  • Mari Palta
  • Brian S. Yandell
  • Michael A. Newton

Abstract

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  • Huageng Tao & Mari Palta & Brian S. Yandell & Michael A. Newton, 1999. "An Estimation Method for the Semiparametric Mixed Effects Model," Biometrics, The International Biometric Society, vol. 55(1), pages 102-110, March.
    • Handle: RePEc:bla:biomet:v:55:y:1999:i:1:p:102-110
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.1999.00102.x
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    Citations

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    Cited by:

    1. Zhang, Daowen & Davidian, Marie, 2004. "Likelihood and conditional likelihood inference for generalized additive mixed models for clustered data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 90-106, October.
    2. Peter Hall & Tapabrata Maiti, 2008. "Non‐parametric inference for clustered binary and count data when only summary information is available," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 725-738, September.
    3. Peter Hall & Tapabrata Maiti, 2009. "Deconvolution methods for non‐parametric inference in two‐level mixed models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 703-718, June.
    4. Kalyan Das & Mohamad Elmasri & Arusharka Sen, 2016. "A Skew-normal copula-driven GLMM," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 396-413, November.
    5. Xiao Song & Marie Davidian & Anastasios A. Tsiatis, 2002. "A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data," Biometrics, The International Biometric Society, vol. 58(4), pages 742-753, December.
    6. Rendao Ye & Tonghui Wang & Saowanit Sukparungsee & Arjun Gupta, 2015. "Tests in variance components models under skew-normal settings," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(7), pages 885-904, October.
    7. Hartford, Alan & Davidian, Marie, 2000. "Consequences of misspecifying assumptions in nonlinear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 34(2), pages 139-164, August.
    8. Ryan Martin, 2021. "A Survey of Nonparametric Mixing Density Estimation via the Predictive Recursion Algorithm," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 97-121, May.
    9. Ho, Remus K.W. & Hu, Inchi, 2008. "Flexible modelling of random effects in linear mixed models--A Bayesian approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1347-1361, January.
    10. Liang Li & Jun Shao & Mari Palta, 2005. "A Longitudinal Measurement Error Model with a Semicontinuous Covariate," Biometrics, The International Biometric Society, vol. 61(3), pages 824-830, September.
    11. Staudenmayer, John & Ruppert, David & Buonaccorsi, John P., 2008. "Density Estimation in the Presence of Heteroscedastic Measurement Error," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 726-736, June.
    12. Wendimagegn Ghidey & Emmanuel Lesaffre & Paul Eilers, 2004. "Smooth Random Effects Distribution in a Linear Mixed Model," Biometrics, The International Biometric Society, vol. 60(4), pages 945-953, December.
    13. David Todem & KyungMann Kim & Jason Fine & Limin Peng, 2010. "Semiparametric regression models and sensitivity analysis of longitudinal data with non‐random dropouts," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(2), pages 133-156, May.
    14. Yucong Lin & Jinhua Su & Yang Liu & Jue Hou & Feifei Wang, 2024. "Implicit profiling estimation for semiparametric models with bundled parameters," Statistical Papers, Springer, vol. 65(5), pages 3203-3234, July.
    15. Lesperance, Mary & Saab, Rabih & Neuhaus, John, 2014. "Nonparametric estimation of the mixing distribution in logistic regression mixed models with random intercepts and slopes," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 211-219.
    16. Vaidehi Dixit & Ryan Martin, 2022. "Estimating a Mixing Distribution on the Sphere Using Predictive Recursion," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 596-626, November.
    17. Zeinolabedin Najafi & Karim Zare & Mohammad Reza Mahmoudi & Soheil Shokri & Amir Mosavi, 2022. "Inference and Local Influence Assessment in a Multifactor Skew-Normal Linear Mixed Model," Mathematics, MDPI, vol. 10(15), pages 1-21, August.
    18. Vock, David & Davidian, Marie & Tsiatis, Anastasios, 2014. "SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(c02).
    19. Daowen Zhang & Marie Davidian, 2001. "Linear Mixed Models with Flexible Distributions of Random Effects for Longitudinal Data," Biometrics, The International Biometric Society, vol. 57(3), pages 795-802, September.
    20. Forkman Johannes, 2017. "Generalized Confidence Intervals for Intra- and Inter-subject Coefficients of Variation in Linear Mixed-effects Models," The International Journal of Biostatistics, De Gruyter, vol. 13(2), pages 1-14, November.

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