Estimation in partially linear models with missing responses at random

Qihua Wang and Zhihua Sun

Journal of Multivariate Analysis, 2007, vol. 98, issue 7, 1470-1493

Abstract: A partially linear model is considered when the responses are missing at random. Imputation, semiparametric regression surrogate and inverse marginal probability weighted approaches are developed to estimate the regression coefficients and the nonparametric function, respectively. All the proposed estimators for the regression coefficients are shown to be asymptotically normal, and the estimators for the nonparametric function are proved to converge at an optimal rate. A simulation study is conducted to compare the finite sample behavior of the proposed estimators.

Keywords: Imputation; estimator; Regression; surrogate; estimator; Inverse; marginal; probability; weighted; estimator; Asymptotic; normality (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (35)

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