Semi-parametric rank regression with missing responses

Huybrechts F. Bindele and Ash Abebe

Journal of Multivariate Analysis, 2015, vol. 142, issue C, 117-132

Abstract: We consider a semi-parametric regression model with responses missing at random and study the rank estimator of the regression coefficient. Consistency and asymptotic normality of the proposed estimator are established. Monte Carlo simulation experiments show that the proposed estimator is more efficient than the least squares estimator whenever the error distribution is heavy tailed or contaminated. When the errors follow a normal distribution, these simulation experiments show that the rank estimator can be more efficient than its least squares counterpart for cases with large proportion of missing responses.

Keywords: Wilcoxon estimator; Strong consistency; Asymptotic normality; Missing at random; Inverse probability; Simple imputation (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.jmva.2015.08.007

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