Zhang, L., Beyl, R., Burton, J., Johnson, C.M., Han, H. and Johnson, W.D. (2014) A Large Sample Statistical Test for Equality of Percentile Profiles across Multiple Populations. Proceedings of the Joint Statistical Meetings of the American Statistical Association, Biometric Society and Institute of Mathematical Statistics Section on Statistics in Epidemiology, Boston, 2-7 August 2014, 3851-3857.

has been cited by the following article:

• TITLE: Use of Pearson’s Chi-Square for Testing Equality of Percentile Profiles across Multiple Populations

  AUTHORS: William D. Johnson, Robbie A. Beyl, Jeffrey H. Burton, Callie M. Johnson, Jacob E. Romer, Lei Zhang

  KEYWORDS: Asymptotic Chi-Square Test, Equality of Percentiles, Large Sample Test, Median Test, Nonparametric Methods

  JOURNAL NAME: Open Journal of Statistics, Vol.5 No.5, August 5, 2015

  ABSTRACT: In large sample studies where distributions may be skewed and not readily transformed to symmetry, it may be of greater interest to compare different distributions in terms of percentiles rather than means. For example, it may be more informative to compare two or more populations with respect to their within population distributions by testing the hypothesis that their corresponding respective 10th, 50th, and 90th percentiles are equal. As a generalization of the median test, the proposed test statistic is asymptotically distributed as Chi-square with degrees of freedom dependent upon the number of percentiles tested and constraints of the null hypothesis. Results from simulation studies are used to validate the nominal 0.05 significance level under the null hypothesis, and asymptotic power properties that are suitable for testing equality of percentile profiles against selected profile discrepancies for a variety of underlying distributions. A pragmatic example is provided to illustrate the comparison of the percentile profiles for four body mass index distributions.