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Nonparametric Regression With Missing Outcomes Using Weighted Kernel Estimating Equations

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  • Wang, Lu
  • Rotnitzky, Andrea
  • Lin, Xihong

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  • Wang, Lu & Rotnitzky, Andrea & Lin, Xihong, 2010. "Nonparametric Regression With Missing Outcomes Using Weighted Kernel Estimating Equations," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1135-1146.
  • Handle: RePEc:bes:jnlasa:v:105:i:491:y:2010:p:1135-1146
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    File URL: http://pubs.amstat.org/doi/abs/10.1198/jasa.2010.tm08463
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    Cited by:

    1. Chen, Qixuan & Paik, Myunghee Cho & Kim, Minjin & Wang, Cuiling, 2016. "Using link-preserving imputation for logistic partially linear models with missing covariates," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 174-185.
    2. Majid Mojirsheibani & Timothy Reese, 2017. "Kernel regression estimation for incomplete data with applications," Statistical Papers, Springer, vol. 58(1), pages 185-209, March.
    3. Timothy Reese & Majid Mojirsheibani, 2017. "On the $$L_p$$ L p norms of kernel regression estimators for incomplete data with applications to classification," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(1), pages 81-112, March.
    4. Han, Peisong, 2012. "A note on improving the efficiency of inverse probability weighted estimator using the augmentation term," Statistics & Probability Letters, Elsevier, vol. 82(12), pages 2221-2228.
    5. repec:bla:jorssb:v:79:y:2017:i:4:p:1229-1245 is not listed on IDEAS

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