Covariate-balancing-propensity-score-based inference for linear models with missing responses

Donglin Guo, Liugen Xue and Yuqin Hu

Statistics & Probability Letters, 2017, vol. 123, issue C, 139-145

Abstract: Based on covariate balancing propensity score (CBPS), improved estimators for the regression coefficients and population mean of linear models are obtained, when the responses are missing at random. It is proved that the proposed estimators are asymptotically normal.

Keywords: Linear model; Missing at random; Covariate balancing propensity score; GMM; Augmented inverse probability weighted; Robust estimation (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1016/j.spl.2016.12.001

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