p-Value for two-Sample Linear Rank Tests Using Permutation Simulations and the Normal Approximation Method

Abstract

Test statistics from the class of two-sample linear rank tests are commonly used to compare a treatment group with a control group. Two independent random samples of sizes m and n are drawn from two populations. As a result, N = m + n observations in total are obtained. The aim is to test the null hypothesis of identical distributions. The alternative hypothesis is that the populations are of the same form but with a different measure of central tendency. This article examines mid p-values from the null permutation distributions of tests based on the class of two-sample linear rank statistics. The results obtained indicate that normal approximation-based computations are very close to the permutation simulations, and they provide p-values that are close to the exact mid p-values for all practical purposes.

Keywords:

• Linear rank test
• Mid p-value
• Normal approximation
• Permutation distribution

Acknowledgments

The authors thank the referee for constructive comments.

Additional information

Funding

This research was supported financially by Taibah University, AlMadinah-M., Kingdom of Saudi Arabia.