Exact Bahadur Slope for combining independent tests in the case of the Pareto distribution

In this paper, we compared the Exact Bahadur Slope (EBS) and the asymptotic relative efficiency of four combination methods for testing a single hypothesis against a one-sided alternative in the case of Pareto distribution when the number of tests tends to infinity. These methods combine the p-value of the corresponding test into one overall test. Fisher's, logistic, the sum of p-values, and inverse normal procedures are the four techniques used in our study. To study the performance of the combination methods, we derived the EBS expressions and compared the limit ratios locally and for large values of the shape parameter of the Pareto distribution via EBS. We also computed the EBS numerically for when the parameter of interest starts moving from the null space and applied the four methods to real data examples. We found that Fisher's method uniformly dominates the other methods in terms of EBS.