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Empirical likelihood for partially linear models with missing responses at random

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  • Yongsong Qin
  • Jianjun Li

Abstract

Suppose that we have a partially linear model Yi=X′iβ+g(Ti)+εi with E(ε|X, T)=0, where {Xi, Ti, i=1, …, n} are random and observed completely, and {Yi, i=1, …, n} are missing at random (MAR). Empirical likelihood (EL) ratio statistics for the regression coefficient β and the nonparametric function g(t0) for fixed t0∈(0, 1) are constructed based on the inverse probability weighted imputation approach, which asymptotically have χ2-type distributions. These results are used to obtain EL-based confidence regions for β and g(t0). Results of a simulation study on the finite sample performance of EL-based confidence regions are presented.

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  • Yongsong Qin & Jianjun Li, 2011. "Empirical likelihood for partially linear models with missing responses at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 497-511.
    • Handle: RePEc:taf:gnstxx:v:23:y:2011:i:2:p:497-511
    DOI: 10.1080/10485252.2010.531134
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Qiu, Jin & Ma, Qing & Wu, Lang, 2019. "A moving blocks empirical likelihood method for panel linear fixed effects models with serial correlations and cross-sectional dependences," Economic Modelling, Elsevier, vol. 83(C), pages 394-405.

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