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Penalized Estimating Functions and Variable Selection in Semiparametric Regression Models

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  1. Jialiang Li & Qi Zheng & Limin Peng & Zhipeng Huang, 2016. "Survival impact index and ultrahigh‐dimensional model‐free screening with survival outcomes," Biometrics, The International Biometric Society, vol. 72(4), pages 1145-1154, December.
  2. Xiaochao Xia & Binyan Jiang & Jialiang Li & Wenyang Zhang, 2016. "Low-dimensional confounder adjustment and high-dimensional penalized estimation for survival analysis," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(4), pages 547-569, October.
  3. Lee Dasom & Yang Shu & Wang Xiaofei, 2022. "Doubly robust estimators for generalizing treatment effects on survival outcomes from randomized controlled trials to a target population," Journal of Causal Inference, De Gruyter, vol. 10(1), pages 415-440, January.
  4. Zhongzhe Ouyang & Lu Wang & Alzheimer’s Disease Neuroimaging Initiative, 2024. "Imputation-Based Variable Selection Method for Block-Wise Missing Data When Integrating Multiple Longitudinal Studies," Mathematics, MDPI, vol. 12(7), pages 1-14, March.
  5. Xingwei Tong & Xin He & Liuquan Sun & Jianguo Sun, 2009. "Variable Selection for Panel Count Data via Non‐Concave Penalized Estimating Function," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(4), pages 620-635, December.
  6. Zhihua Sun & Yi Liu & Kani Chen & Gang Li, 2022. "Broken adaptive ridge regression for right-censored survival data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(1), pages 69-91, February.
  7. Zangdong He & Wanzhu Tu & Sijian Wang & Haoda Fu & Zhangsheng Yu, 2015. "Simultaneous variable selection for joint models of longitudinal and survival outcomes," Biometrics, The International Biometric Society, vol. 71(1), pages 178-187, March.
  8. Hu, Jianwei & Chai, Hao, 2013. "Adjusted regularized estimation in the accelerated failure time model with high dimensional covariates," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 96-114.
  9. Lan Wang & Jianhui Zhou & Annie Qu, 2012. "Penalized Generalized Estimating Equations for High-Dimensional Longitudinal Data Analysis," Biometrics, The International Biometric Society, vol. 68(2), pages 353-360, June.
  10. Fengting Yi & Niansheng Tang & Jianguo Sun, 2022. "Simultaneous variable selection and estimation for joint models of longitudinal and failure time data with interval censoring," Biometrics, The International Biometric Society, vol. 78(1), pages 151-164, March.
  11. Bingduo Yang & Christian M. Hafner & Guannan Liu & Wei Long, 2021. "Semiparametric estimation and variable selection for single‐index copula models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 962-988, November.
  12. 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.
  13. Zhixuan Fu & Chirag R. Parikh & Bingqing Zhou, 2017. "Penalized variable selection in competing risks regression," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 353-376, July.
  14. Weibin Mo & Yufeng Liu, 2022. "Efficient learning of optimal individualized treatment rules for heteroscedastic or misspecified treatment‐free effect models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 440-472, April.
  15. Peng Lai & Fangjian Wang & Tingyu Zhu & Qingzhao Zhang, 2021. "Model identification and selection for single-index varying-coefficient models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 457-480, June.
  16. Yongjin Li & Qingzhao Zhang & Qihua Wang, 2017. "Penalized estimation equation for an extended single-index model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 169-187, February.
  17. Wang, Li & Wang, Suojin & Wang, Guannan, 2014. "Variable selection and estimation for longitudinal survey data," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 409-424.
  18. Dasom Lee & Shu Yang & Lin Dong & Xiaofei Wang & Donglin Zeng & Jianwen Cai, 2023. "Improving trial generalizability using observational studies," Biometrics, The International Biometric Society, vol. 79(2), pages 1213-1225, June.
  19. Cai, Zongwu & Juhl, Ted & Yang, Bingduo, 2015. "Functional index coefficient models with variable selection," Journal of Econometrics, Elsevier, vol. 189(2), pages 272-284.
  20. 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.
  21. 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.
  22. Huaihou Chen & Donglin Zeng & Yuanjia Wang, 2017. "Penalized nonlinear mixed effects model to identify biomarkers that predict disease progression," Biometrics, The International Biometric Society, vol. 73(4), pages 1343-1354, December.
  23. Blommaert, A. & Hens, N. & Beutels, Ph., 2014. "Data mining for longitudinal data under multicollinearity and time dependence using penalized generalized estimating equations," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 667-680.
  24. Zhang, Hao Helen & Lu, Wenbin & Wang, Hansheng, 2010. "On sparse estimation for semiparametric linear transformation models," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1594-1606, August.
  25. Tamar Sofer & Elizabeth D. Schifano & David C. Christiani & Xihong Lin, 2017. "Weighted pseudolikelihood for SNP set analysis with multiple secondary outcomes in case‐control genetic association studies," Biometrics, The International Biometric Society, vol. 73(4), pages 1210-1220, December.
  26. Feng, Sanying & Xue, Liugen, 2015. "Model detection and estimation for single-index varying coefficient model," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 227-244.
  27. 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).
  28. Hongyu An & Boping Tian, 2024. "Varying Index Coefficient Model for Tail Index Regression," Mathematics, MDPI, vol. 12(13), pages 1-34, June.
  29. Zhangong Zhou & Rong Jiang & Weimin Qian, 2013. "LAD variable selection for linear models with randomly censored data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(2), pages 287-300, February.
  30. Ouyang, Jiangrong & Bondell, Howard, 2023. "Bayesian analysis of longitudinal data via empirical likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
  31. Zhao, Weihua & Lian, Heng & Zhang, Riquan & Lai, Peng, 2016. "Estimation and variable selection for proportional response data with partially linear single-index models," Computational Statistics & Data Analysis, Elsevier, vol. 96(C), pages 40-56.
  32. Chung-Wei Shen & Yi-Hau Chen, 2012. "Model Selection for Generalized Estimating Equations Accommodating Dropout Missingness," Biometrics, The International Biometric Society, vol. 68(4), pages 1046-1054, December.
  33. Xiaobo Wang & Jiayu Huang & Guosheng Yin & Jian Huang & Yuanshan Wu, 2023. "Double bias correction for high-dimensional sparse additive hazards regression with covariate measurement errors," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 115-141, January.
  34. Joseph G. Ibrahim & Hongtu Zhu & Ramon I. Garcia & Ruixin Guo, 2011. "Fixed and Random Effects Selection in Mixed Effects Models," Biometrics, The International Biometric Society, vol. 67(2), pages 495-503, June.
  35. Feng, Sanying & He, Wenqi & Li, Feng, 2020. "Model detection and estimation for varying coefficient panel data models with fixed effects," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
  36. Yue Mu & Li Jialiang, 2017. "Improvement Screening for Ultra-High Dimensional Data with Censored Survival Outcomes and Varying Coefficients," The International Journal of Biostatistics, De Gruyter, vol. 13(1), pages 1-16, May.
  37. Fan, Yali & Qin, Guoyou & Zhu, Zhongyi, 2012. "Variable selection in robust regression models for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 156-167.
  38. Li, Li & Shi, Pengfei & Fan, Qingliang & Zhong, Wei, 2024. "Causal effect estimation with censored outcome and covariate selection," Statistics & Probability Letters, Elsevier, vol. 204(C).
  39. Liang, Lixing & Zhuang, Yipeng & Yu, Philip L.H., 2024. "Variable selection for high-dimensional incomplete data," Computational Statistics & Data Analysis, Elsevier, vol. 192(C).
  40. Cheng, Chao & Feng, Xingdong & Huang, Jian & Jiao, Yuling & Zhang, Shuang, 2022. "ℓ0-Regularized high-dimensional accelerated failure time model," Computational Statistics & Data Analysis, Elsevier, vol. 170(C).
  41. Brent A. Johnson & Qi Long & Matthias Chung, 2011. "On Path Restoration for Censored Outcomes," Biometrics, The International Biometric Society, vol. 67(4), pages 1379-1388, December.
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