B1396
Title: Marginal estimation under a partially linear model with missing observations
Authors: Ana Perez Gonzalez - University of Vigo (Spain) [presenting]
Graciela Boente - Universidad de Buenos Aires (Argentina)
Ana Maria Bianco - Universidad de Buenos Aires (Argentina)
Wenceslao Gonzalez-Manteiga - University of Santiago de Compostela (Spain)
Abstract: A semiparametric partially linear regression model is considered where missing data occur in the response and in the covariates corresponding to the linear component. The aim is to estimate a marginal functional, such as the mean, the median or any $\alpha-$quantile. A missing at random (MAR) condition is assumed in order to prevent from bias in the estimation of the marginal measures under a non-ignorable missing mechanism. A three stepwise procedure is employed to estimate the parametric and nonparametric components, while different approaches are given for the estimation of the marginal functional of interest. Through a Monte Carlo study we compare the performance of the given proposals.
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