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Empirical‐likelihood‐based inference in missing response problems and its application in observational studies

Citations

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  1. Liu, Tianqing & Yuan, Xiaohui & Li, Zhaohai & Li, Yuanzhang, 2013. "Empirical and weighted conditional likelihoods for matched case-control studies with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 185-199.
  2. Satoshi Hattori & Masayuki Henmi, 2014. "Stratified doubly robust estimators for the average causal effect," Biometrics, The International Biometric Society, vol. 70(2), pages 270-277, June.
  3. 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.
  4. Wang, Qihua & Su, Miaomiao & Wang, Ruoyu, 2021. "A beyond multiple robust approach for missing response problem," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
  5. Peisong Han, 2016. "Intrinsic efficiency and multiple robustness in longitudinal studies with drop-out," Biometrika, Biometrika Trust, vol. 103(3), pages 683-700.
  6. Bryan S. Graham & Cristine Campos de Xavier Pinto & Daniel Egel, 2016. "Efficient Estimation of Data Combination Models by the Method of Auxiliary-to-Study Tilting (AST)," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 288-301, April.
  7. 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.
  8. Biao Zhang, 2016. "Empirical Likelihood in Causal Inference," Econometric Reviews, Taylor & Francis Journals, vol. 35(2), pages 201-231, February.
  9. Jing Cheng & Dylan S. Small, 2021. "Semiparametric models and inference for the effect of a treatment when the outcome is nonnegative with clumping at zero," Biometrics, The International Biometric Society, vol. 77(4), pages 1187-1201, December.
  10. Peisong Han & Linglong Kong & Jiwei Zhao & Xingcai Zhou, 2019. "A general framework for quantile estimation with incomplete data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 81(2), pages 305-333, April.
  11. Li, Wei & Luo, Shanshan & Xu, Wangli, 2024. "Calibrated regression estimation using empirical likelihood under data fusion," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).
  12. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
  13. Han, Peisong & Song, Peter X.-K. & Wang, Lu, 2015. "Achieving semiparametric efficiency bound in longitudinal data analysis with dropouts," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 59-70.
  14. Liugen Xue, 2009. "Empirical Likelihood Confidence Intervals for Response Mean with Data Missing at Random," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(4), pages 671-685, December.
  15. 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.
  16. Xue, Liugen & Zhang, Jinghua, 2020. "Empirical likelihood for partially linear single-index models with missing observations," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  17. Xue, Liugen, 2009. "Empirical likelihood for linear models with missing responses," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1353-1366, August.
  18. Takahiro Hoshino & Ryosuke Igari, 2017. "Quasi-Bayesian Inference for Latent Variable Models with External Information: Application to generalized linear mixed models for biased data," Keio-IES Discussion Paper Series 2017-014, Institute for Economics Studies, Keio University.
  19. Karun Adusumilli & Taisuke Otsu & Chen Qiu, 2020. "Reweighted nonparametric likelihood inference for linear functionals," STICERD - Econometrics Paper Series 614, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  20. Peisong Han, 2016. "Combining Inverse Probability Weighting and Multiple Imputation to Improve Robustness of Estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 246-260, March.
  21. Shixiao Zhang & Peisong Han & Changbao Wu, 2023. "Calibration Techniques Encompassing Survey Sampling, Missing Data Analysis and Causal Inference," International Statistical Review, International Statistical Institute, vol. 91(2), pages 165-192, August.
  22. Tianqing Liu & Xiaohui Yuan, 2020. "Empirical likelihood-based weighted rank regression with missing covariates," Statistical Papers, Springer, vol. 61(2), pages 697-725, April.
  23. Hamori, Shigeyuki & Motegi, Kaiji & Zhang, Zheng, 2019. "Calibration estimation of semiparametric copula models with data missing at random," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 85-109.
  24. Adusumilli, Karun & Otsu, Taisuke & Qiu, Chen, 2023. "Reweighted nonparametric likelihood inference for linear functionals," LSE Research Online Documents on Economics 120198, London School of Economics and Political Science, LSE Library.
  25. Karun Adusumilli & Taisuke Otsu, 2018. "Likelihood ratio inference for missing data models," STICERD - Econometrics Paper Series 599, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  26. 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.
  27. Zhong Guan & Jing Qin, 2017. "Empirical likelihood method for non-ignorable missing data problems," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 113-135, January.
  28. Bryan S. Graham & Cristine Campos De Xavier Pinto & Daniel Egel, 2012. "Inverse Probability Tilting for Moment Condition Models with Missing Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 1053-1079.
  29. Shengfang Tang & Zongwu Cai & Ying Fang & Ming Lin, 2019. "Testing Unconfoundedness Assumption Using Auxiliary Variables," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201905, University of Kansas, Department of Economics, revised Mar 2019.
  30. Zhang, Xiaoke & Xue, Wu & Wang, Qiyue, 2021. "Covariate balancing functional propensity score for functional treatments in cross-sectional observational studies," Computational Statistics & Data Analysis, Elsevier, vol. 163(C).
  31. Xiaogang Duan & Guosheng Yin, 2017. "Ensemble Approaches to Estimating the Population Mean with Missing Response," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 899-917, December.
  32. Kwun Chuen Gary Chan & Sheung Chi Phillip Yam & Zheng Zhang, 2016. "Globally efficient non-parametric inference of average treatment effects by empirical balancing calibration weighting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 673-700, June.
  33. Jaeger, Adam & Lazar, Nicole A., 2020. "Split sample empirical likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
  34. Wei, Yuting & Wang, Qihua, 2021. "Cross-validation-based model averaging in linear models with response missing at random," Statistics & Probability Letters, Elsevier, vol. 171(C).
  35. 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.
  36. 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.
  37. Zhao, Yichuan & Chen, Feiming, 2008. "Empirical likelihood inference for censored median regression model via nonparametric kernel estimation," Journal of Multivariate Analysis, Elsevier, vol. 99(2), pages 215-231, February.
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