Sampling Importance Resampling Algorithm with Nonignorable Missing Response Variable Based on Smoothed Quantile Regression
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- Joel L. Horowitz, 1998.
"Bootstrap Methods for Median Regression Models,"
Econometrica, Econometric Society, vol. 66(6), pages 1327-1352, November.
- Joel L. Horowitz, 1996. "Bootstrap Methods for Median Regression Models," Econometrics 9608004, University Library of Munich, Germany.
- Whitney K. Newey & Richard J. Smith, 2004.
"Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators,"
Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
- Whitney K. Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Min Zhang & Anastasios A. Tsiatis & Marie Davidian, 2008. "Improving Efficiency of Inferences in Randomized Clinical Trials Using Auxiliary Covariates," Biometrics, The International Biometric Society, vol. 64(3), pages 707-715, September.
- Jun Shao & Lei Wang, 2016. "Semiparametric inverse propensity weighting for nonignorable missing data," Biometrika, Biometrika Trust, vol. 103(1), pages 175-187.
- Jae Kwang Kim, 2011. "Parametric fractional imputation for missing data analysis," Biometrika, Biometrika Trust, vol. 98(1), pages 119-132.
- Kim, Jae Kwang & Yu, Cindy Long, 2011. "A Semiparametric Estimation of Mean Functionals With Nonignorable Missing Data," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 157-165.
- repec:mpr:mprres:8160 is not listed on IDEAS
- Xuerong Chen & Alan T. K. Wan & Yong Zhou, 2015. "Efficient Quantile Regression Analysis With Missing Observations," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(510), pages 723-741, June.
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Keywords
empirical likelihood; nonignorable missing; quantile regression; sampling importance resampling;All these keywords.
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