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Penalized Generalized Estimating Equations for High-Dimensional Longitudinal Data Analysis

Citations

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Cited by:

  1. Xiaorui Zhu & Yichen Qin & Peng Wang, 2023. "Sparsified Simultaneous Confidence Intervals for High-Dimensional Linear Models," Papers 2307.07574, arXiv.org, revised Jan 2025.
  2. Hu, Yuao & Lian, Heng, 2013. "Variable selection in a partially linear proportional hazards model with a diverging dimensionality," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 61-69.
  3. Brittany Green & Heng Lian & Yan Yu & Tianhai Zu, 2021. "Ultra high‐dimensional semiparametric longitudinal data analysis," Biometrics, The International Biometric Society, vol. 77(3), pages 903-913, September.
  4. Jakub Stoklosa & Heloise Gibb & David I. Warton, 2014. "Fast forward selection for generalized estimating equations with a large number of predictor variables," Biometrics, The International Biometric Society, vol. 70(1), pages 110-120, March.
  5. Zhang, Shen & Zhao, Peixin & Li, Gaorong & Xu, Wangli, 2019. "Nonparametric independence screening for ultra-high dimensional generalized varying coefficient models with longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 37-52.
  6. Yang, Yuan & McMahan, Christopher S. & Wang, Yu-Bo & Ouyang, Yuyuan, 2024. "Estimation of l0 norm penalized models: A statistical treatment," Computational Statistics & Data Analysis, Elsevier, vol. 192(C).
  7. Lv, Jing & Yang, Hu & Guo, Chaohui, 2015. "An efficient and robust variable selection method for longitudinal generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 74-88.
  8. Heng Lian & Peng Lai & Hua Liang, 2013. "Partially Linear Structure Selection in Cox Models with Varying Coefficients," Biometrics, The International Biometric Society, vol. 69(2), pages 348-357, June.
  9. Wang, Kangning & Li, Shaomin & Sun, Xiaofei & Lin, Lu, 2019. "Modal regression statistical inference for longitudinal data semivarying coefficient models: Generalized estimating equations, empirical likelihood and variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 257-276.
  10. Ke, Baofang & Zhao, Weihua & Wang, Lei, 2023. "Smoothed tensor quantile regression estimation for longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
  11. Huang, Youjun & Pan, Jianxin, 2021. "Joint generalized estimating equations for longitudinal binary data," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
  12. Li, Gaorong & Lian, Heng & Feng, Sanying & Zhu, Lixing, 2013. "Automatic variable selection for longitudinal generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 174-186.
  13. Lian, Heng & Li, Jianbo & Tang, Xingyu, 2014. "SCAD-penalized regression in additive partially linear proportional hazards models with an ultra-high-dimensional linear part," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 50-64.
  14. Rahul Ghosal & Arnab Maity & Timothy Clark & Stefano B. Longo, 2020. "Variable selection in functional linear concurrent regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 565-587, June.
  15. Kangning Wang & Wen Shan, 2021. "Copula and composite quantile regression-based estimating equations for longitudinal data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 441-455, June.
  16. Geronimi, J. & Saporta, G., 2017. "Variable selection for multiply-imputed data with penalized generalized estimating equations," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 103-114.
  17. Green, Brittany & Lian, Heng & Yu, Yan & Zu, Tianhai, 2023. "Semiparametric penalized quadratic inference functions for longitudinal data in ultra-high dimensions," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
  18. Zhang, Yaohua & Zou, Jian & Ravishanker, Nalini & Thavaneswaran, Aerambamoorthy, 2019. "Modeling financial durations using penalized estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 145-158.
  19. Ouyang, Jiangrong & Bondell, Howard, 2023. "Bayesian analysis of longitudinal data via empirical likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
  20. Gregory Vaughan & Robert Aseltine & Kun Chen & Jun Yan, 2017. "Stagewise generalized estimating equations with grouped variables," Biometrics, The International Biometric Society, vol. 73(4), pages 1332-1342, December.
  21. Li, Cheng & Jiang, Wenxin, 2016. "On oracle property and asymptotic validity of Bayesian generalized method of moments," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 132-147.
  22. Qin, Yichen & Wang, Linna & Li, Yang & Li, Rong, 2023. "Visualization and assessment of model selection uncertainty," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
  23. Fang, Jianglin, 2023. "A split-and-conquer variable selection approach for high-dimensional general semiparametric models with massive data," Journal of Multivariate Analysis, Elsevier, vol. 194(C).
  24. Woncheol Jang, 2013. "Generalized Estimating Equations by HARDIN, J. W. and HILBE, J. M," Biometrics, The International Biometric Society, vol. 69(3), pages 799-799, September.
  25. Lu Tang & Peter X.‐K. Song, 2021. "Poststratification fusion learning in longitudinal data analysis," Biometrics, The International Biometric Society, vol. 77(3), pages 914-928, September.
  26. Lv, Jing & Guo, Chaohui & Yang, Hu & Li, Yalian, 2017. "A moving average Cholesky factor model in covariance modeling for composite quantile regression with longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 129-144.
  27. Wenning Feng & Abdhi Sarkar & Chae Young Lim & Tapabrata Maiti, 2016. "Variable selection for binary spatial regression: Penalized quasi‐likelihood approach," Biometrics, The International Biometric Society, vol. 72(4), pages 1164-1172, December.
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