JSM 2004 - Toronto

Abstract #301578

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Activity Number: 110
Type: Contributed
Date/Time: Monday, August 9, 2004 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #301578
Title: Robust Testing in Unbalanced Heteroscedastic One-way Random Effects Models Using an R-estimator
Author(s): Inkyung Jung*+ and Pranab K. Sen
Companies: University of North Carolina, Chapel Hill and University of North Carolina, Chapel Hill
Address: , , ,
Keywords:
Abstract:

For testing the significance of random effect in the one-way random effect model, F-tests can be conducted under normality. However, if the normality assumption is violated, the F-tests may be inefficient and even inconsistent in some cases. Moreover, for heteroscedastic data, an exact F-test statistic cannot be constructed even under normality and test statistics having only approximately F distributions have been suggested. A robust rank-based test, assuming only symmetric but otherwise arbitrary continuous distributions for the random effect and random errors, is proposed here. The proposed testing procedure eliminates the need to estimate other nuisance parameters, which is required for parametric F-tests. This testing procedure is based on normal distributional approximation. Simulation studies suggest that for significance level, the proposed test is much more robust than F-tests against heteroscedasticity, unbalancedness, and departures from normality.

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