JSM 2005 - Toronto

Abstract #304409

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 362
Type: Contributed
Date/Time: Wednesday, August 10, 2005 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract - #304409
Title: Rank Regression Inference via Empirical Likelihood
Author(s): Ellen Bishop*+
Companies: RTI International
Address: Atlanta Kroger Center Oxford Building, Atlanta, GA, 30341, United States
Keywords: empirical likelihood ratio ; rank regression
Abstract:

Rank regression has been developed as an alternative semiparametric method for statistical analysis when the assumptions of parametric methods are not sufficiently met, such as normality of the residuals or constant variance.This paper will explore estimating beta by minimizing the dispersion function. It also develops confidence intervals using an empirical likelihood (EL) ratio method and presents coverage probabilities. EL has the advantage of not requiring variance estimation, which is required for the normal approximation method. Simulation studies are used to compare and evaluate normal approximation versus EL inference methods for various conditions such as sample size or error distribution. Simulation results reveal conditions when the EL method results in a coverage probability closer to the true significance level than the normal approximation method. An application of stability analysis also shows the EL method to result in shorter confidence intervals for real-life data.

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