An Optimal Nonparametric Test of Symmetry Based on the Overlapping Coefficient Using an Extreme Ranked Set Sample: Application to Noninvasive Measurement of Cardiac Output by Electrical Velocimetry in Neonates
Document Type
Presentation
Presentation Date
11-2-2011
Abstract or Description
In this paper we provide a more efficient nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation applied to an extreme ranked set sample. Our investigation reveals that our proposed test of symmetry is more powerful than all available tests of symmetry. Intensive simulation is conducted to examine the power of the proposed test. An illustration is provided using cardiac output and body weight of neonates in a neonatal intensive care unit.
Sponsorship/Conference/Institution
American Public Health Association Annual Conference (APHA)
Location
Washington, DC
Recommended Citation
Samawi, Hani M., Robert L. Vogel.
2011.
"An Optimal Nonparametric Test of Symmetry Based on the Overlapping Coefficient Using an Extreme Ranked Set Sample: Application to Noninvasive Measurement of Cardiac Output by Electrical Velocimetry in Neonates."
Biostatistics Faculty Presentations.
Presentation 24.
https://digitalcommons.georgiasouthern.edu/biostat-facpres/24
