A More Efficient Nonparametric Test of Symmetry Based on the Overlapping Coefficient Using Extreme Ranked Set Sample
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 order statistics, namely extreme ranked set sampling. Our simulation investigation reveals that our proposed test of symmetry is at least as powerful as currently 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.
Eastern North American Region International Biometric Society Annual Conference (ENAR)
Vogel, Robert L., Hani M. Samawi.
"A More Efficient Nonparametric Test of Symmetry Based on the Overlapping Coefficient Using Extreme Ranked Set Sample."
Biostatistics Faculty Presentations.