We conducted a simulation study to evaluate the performance of the four methods reviewed (MANOVA, PCA, GEE, and TATES) as well as the methods based on the Fisher combination function. In the simulation, we adopted four different approaches to calculating the p-value of the Fisher combination test: FC-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\chi _{2m}^{2}$\end{document}χ2m2: the chi-squared distribution with 2m degrees of freedom under the independence assumption.FC-Permutation: the permutation method based on 1000 permutes.FC-Pearson: the proposed method with the correlation \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\hat {\rho }_{\text {\textit {j,k}}}$\end{document}ρ^j,k being estimated by the Pearson’s sample correlation coefficient.FC-Kendall: the proposed method with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\hat {\rho }_{\text {\textit {j,k}}}$\end{document}ρ^j,k being estimated by the Kendall’s τ.
