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Partially linear models with missing response variables and error-prone covariates

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Cited by:

  1. Wang, Qihua & Lai, Peng, 2011. "Empirical likelihood calibration estimation for the median treatment difference in observational studies," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1596-1609, April.
  2. Su, Haiyan & Liang, Hua, 2010. "An empirical likelihood-based method for comparison of treatment effects--Test of equality of coefficients in linear models," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1079-1088, April.
  3. Bindele, Huybrechts F., 2018. "Covariates missing at random under signed-rank inference," Econometrics and Statistics, Elsevier, vol. 8(C), pages 78-93.
  4. Xiaofeng Lv & Rui Li, 2013. "Smoothed empirical likelihood analysis of partially linear quantile regression models with missing response variables," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 317-347, October.
  5. Baojiang Chen & Xiao-Hua Zhou, 2013. "Generalized Partially Linear Models for Incomplete Longitudinal Data In the Presence of Population-Level Information," Biometrics, The International Biometric Society, vol. 69(2), pages 386-395, June.
  6. Wanrong Liu & Xuewen Lu, 2011. "Empirical likelihood for density-weighted average derivatives," Statistical Papers, Springer, vol. 52(2), pages 391-412, May.
  7. Sun, Zhihua & Ye, Xue & Sun, Liuquan, 2015. "Consistent test of error-in-variables partially linear model with auxiliary variables," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 118-131.
  8. Ash Abebe & Huybrechts F. Bindele & Masego Otlaadisa & Boikanyo Makubate, 2021. "Robust estimation of single index models with responses missing at random," Statistical Papers, Springer, vol. 62(5), pages 2195-2225, October.
  9. Zhimeng Sun & Zhi Su & Jingyi Ma, 2014. "Focused vector information criterion model selection and model averaging regression with missing response," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(3), pages 415-432, April.
  10. Majid Mojirsheibani & Timothy Reese, 2017. "Kernel regression estimation for incomplete data with applications," Statistical Papers, Springer, vol. 58(1), pages 185-209, March.
  11. Yan-Ting Xiao & Fu-Xiao Li, 2020. "Estimation in partially linear varying-coefficient errors-in-variables models with missing response variables," Computational Statistics, Springer, vol. 35(4), pages 1637-1658, December.
  12. Salim Bouzebda & Youssouf Souddi & Fethi Madani, 2024. "Weak Convergence of the Conditional Set-Indexed Empirical Process for Missing at Random Functional Ergodic Data," Mathematics, MDPI, vol. 12(3), pages 1-22, January.
  13. Huixia Judy Wang & Leonard A. Stefanski & Zhongyi Zhu, 2012. "Corrected-loss estimation for quantile regression with covariate measurement errors," Biometrika, Biometrika Trust, vol. 99(2), pages 405-421.
  14. Wangli Xu & Xu Guo & Lixing Zhu, 2012. "Goodness-of-fitting for partial linear model with missing response at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(1), pages 103-118.
  15. Xiaohui Liu & Zhizhong Wang & Xuemei Hu, 2011. "Testing heteroscedasticity in partially linear models with missing covariates," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 321-337.
  16. Jianhong Shi & Fanrong Zhao, 2018. "Statistical inference for heteroscedastic semi-varying coefficient EV models under restricted condition," Statistical Papers, Springer, vol. 59(2), pages 487-511, June.
  17. Bianco, Ana M. & Boente, Graciela & González-Manteiga, Wenceslao & Pérez-González, Ana, 2015. "Robust inference in partially linear models with missing responses," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 88-98.
  18. Zhao, Haibing & You, Jinhong, 2011. "Difference based estimation for partially linear regression models with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1321-1338, November.
  19. Peixin Zhao & Xiaoshuang Zhou, 2018. "Robust empirical likelihood for partially linear models via weighted composite quantile regression," Computational Statistics, Springer, vol. 33(2), pages 659-674, June.
  20. Tang, Niansheng & Wang, Wenjun, 2019. "Robust estimation of generalized estimating equations with finite mixture correlation matrices and missing covariates at random for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 640-655.
  21. Nian-Sheng Tang & Pu-Ying Zhao, 2013. "Empirical likelihood semiparametric nonlinear regression analysis for longitudinal data with responses missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(4), pages 639-665, August.
  22. Nengxiang Ling & Rui Kan & Philippe Vieu & Shuyu Meng, 2019. "Semi-functional partially linear regression model with responses missing at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(1), pages 39-70, January.
  23. Tang, Linjun & Zhou, Zhangong & Wu, Changchun, 2013. "Testing the linear errors-in-variables model with randomly censored data," Statistics & Probability Letters, Elsevier, vol. 83(3), pages 875-884.
  24. Biao Zhang, 2016. "Empirical Likelihood in Causal Inference," Econometric Reviews, Taylor & Francis Journals, vol. 35(2), pages 201-231, February.
  25. Lu Wang & Zhongzhe Ouyang & Xihong Lin, 2024. "Doubly Robust Estimation and Semiparametric Efficiency in Generalized Partially Linear Models with Missing Outcomes," Stats, MDPI, vol. 7(3), pages 1-20, August.
  26. Nengxiang Ling & Lilei Cheng & Philippe Vieu & Hui Ding, 2022. "Missing responses at random in functional single index model for time series data," Statistical Papers, Springer, vol. 63(2), pages 665-692, April.
  27. Boumahdi, Mounir & Ouassou, Idir & Rachdi, Mustapha, 2023. "Estimation in nonparametric functional-on-functional models with surrogate responses," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
  28. Lu, Xuewen, 2009. "Empirical likelihood for heteroscedastic partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 387-396, March.
  29. Zhang, Weiwei & Li, Gaorong & Xue, Liugen, 2011. "Profile inference on partially linear varying-coefficient errors-in-variables models under restricted condition," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 3027-3040, November.
  30. Yu Shen & Han-Ying Liang, 2018. "Quantile regression and its empirical likelihood with missing response at random," Statistical Papers, Springer, vol. 59(2), pages 685-707, June.
  31. Firouzeh Noghrehchi & Jakub Stoklosa & Spiridon Penev, 2020. "Multiple imputation and functional methods in the presence of measurement error and missingness in explanatory variables," Computational Statistics, Springer, vol. 35(3), pages 1291-1317, September.
  32. Xie Yanmei & Zhang Biao, 2017. "Empirical Likelihood in Nonignorable Covariate-Missing Data Problems," The International Journal of Biostatistics, De Gruyter, vol. 13(1), pages 1-20, May.
  33. Dengke Xu & Jiang Du, 2020. "Nonparametric quantile regression estimation for functional data with responses missing at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(8), pages 977-990, November.
  34. Bianco, Ana M. & Spano, Paula M., 2017. "Robust estimation in partially linear errors-in-variables models," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 46-64.
  35. Wangli Xu & Xu Guo, 2013. "Checking the adequacy of partial linear models with missing covariates at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(3), pages 473-490, June.
  36. Xue, Liugen & Xue, Dong, 2011. "Empirical likelihood for semiparametric regression model with missing response data," Journal of Multivariate Analysis, Elsevier, vol. 102(4), pages 723-740, April.
  37. Sima Sharghi & Kevin Stoll & Wei Ning, 2024. "Statistical inferences for missing response problems based on modified empirical likelihood," Statistical Papers, Springer, vol. 65(7), pages 4079-4120, September.
  38. Justin Chown & Ursula U. Müller, 2013. "Efficiently estimating the error distribution in nonparametric regression with responses missing at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(3), pages 665-677, September.
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