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

Hani M. Samawi; Robert L. Vogel

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

Georgia Southern University

Research output: Contribution to conference › Presentation

Abstract

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.

Original language	American English
State	Published - Nov 2 2011
Event	American Public Health Association Annual Conference (APHA) - Duration: Nov 1 2016 → …

Conference

Conference	American Public Health Association Annual Conference (APHA)
Period	11/1/16 → …

Keywords

Nonparametric test
Symmetry
Overlapping coefficient
Ranked set sample application
Noninvasive measurement
Cardiac output
Electrical velocimetry
Neonates

DC Disciplines

Biostatistics
Public Health

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Samawi, H. M., & Vogel, R. L. (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. American Public Health Association Annual Conference (APHA). https://apha.confex.com/apha/139am/webprogram/Paper235688.html

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abstract = " 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.",

keywords = "Nonparametric test, Symmetry, Overlapping coefficient, Ranked set sample application, Noninvasive measurement, Cardiac output, Electrical velocimetry, Neonates",

author = "Samawi, {Hani M.} and Vogel, {Robert L.}",

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Samawi, HM & Vogel, RL 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', American Public Health Association Annual Conference (APHA), 11/1/16. <https://apha.confex.com/apha/139am/webprogram/Paper235688.html>

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. / Samawi, Hani M.; Vogel, Robert L.
2011. American Public Health Association Annual Conference (APHA).

Research output: Contribution to conference › Presentation

TY - CONF

T1 - 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

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AU - Vogel, Robert L.

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KW - Nonparametric test

KW - Symmetry

KW - Overlapping coefficient

KW - Ranked set sample application

KW - Noninvasive measurement

KW - Cardiac output

KW - Electrical velocimetry

KW - Neonates

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T2 - American Public Health Association Annual Conference (APHA)

Y2 - 1 November 2016

ER -

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

Abstract

Conference

Keywords

DC Disciplines

UN SDGs

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