Adaptive Robust Profile Analysis of a Longitudinal Data
Gabriel Asare Okyere
Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Silverius Kwasi Bruku
Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Richard Tawiah *
School of Medicine, Grith University, Brisbane, Australia
Gilbert Biney
Department of Statistics, University for Development Studies, Tamale, Ghana
*Author to whom correspondence should be addressed.
Abstract
This paper uses nine winsorized scores in the adaptive test of Hogg, Fisher and Randles and deals with its extension to hypothesis testing in profile analysis of a balanced longitudinal data. Simulation studies are conducted to evaluate the efficiency of the adaptive test procedure relative to the traditional ANOVA-F test for different non-normal data sets. To illustrate the feasibility of the test, we analyzed a real data set from the study of tumor sizes in mice.
Keywords: Adaptive test, longitudinal data, selector statistic, skewness, tail-weight