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Abstract Details

Activity Number: 124
Type: Contributed
Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract - #305816
Title: Testing for Superiority of Two Regression Curves with Responses Missing at Random
Author(s): Xiaoyu Li*+
Companies: Michigan State University
Address: A413 Wells Hall, East Lansing, MI, 48824, United States
Keywords: missing at random ; nonparametric regression ; kernel estimator
Abstract:

This paper considers the problem of testing the equality of two nonparametric regression curves against a one-sided alternatives based on two samples with possibly distinct design and error densities, with responses missing at random. The paper proposes a class of tests using imputation and covariate matching. The asymptotic distributions of these test statistics are shown to be Gaussian under null hypothesis and a class of local alternatives. The consistency of these tests against a large class of fixed alternatives is also established. The paper also includes a simulation study, which assesses the finite sample behavior of a member of this class of tests.


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