JSM 2005 - Toronto

Abstract #304655

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 137
Type: Contributed
Date/Time: Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #304655
Title: Transforming Skewed Data and the Bootstrap
Author(s): Abu Minhajuddin*+ and Nasratun Nayeem and William R. Schucany
Companies: The University of Texas Southwestern Medical Center at Dallas and Southern Methodist University and Southern Methodist University
Address: 8610 Southwestrn Blvd, Dallas, TX, 75206, United States
Keywords: Bootstrap ; Nonparametric ; Robust methods ; Skewed data ; Transformation
Abstract:

There are times when the available data are skewed. In such situations, practitioners may look for a suitable transformation to symmetry. Robust parametric statistical methods may then be used with the transformed data. However, finding the right transformation is not always an easy task. In this paper, we show the nonparametric bootstrap may be a viable alternative in such a situation. We present simulation results of the relative efficiency of the nonparametric bootstrap when appropriate transformations exist. For the cases where no such transformation is available, nonparametric bootstrap methods may be the only valid procedure.

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