Robust tests for the mean difference in paired data by using bootstrap resampling technique

Abstract EN

The paired sample t-test for testing the difference between two means in paired data is not robust against the violation of the normality assumption.

In this paper, some alternative robust tests have been suggested by using the bootstrap method in addition to combining the bootstrap method with the W.

M test.

Monte Carlo simulation experiments were employed to study the performance of the test statistics of each of these three tests depending on type one error rates and the power rates of the test statistics.

The three tests have been applied on different sample sizes generated from three distributions represented by Bivariate normal distribution, Bivariate contaminated normal distribution, and the Bivariate Exponential The paired sample t-test for testing the difference between two means in paired data is not robust against the violation of the normality assumption.

In this paper, some alternative robust tests have been suggested by using the bootstrap method in addition to combining the bootstrap method with the W.

M test.

Monte Carlo simulation experiments were employed to study the performance of the test statistics of each of these three tests depending on type one error rates and the power rates of the test statistics.

The three tests have been applied on different sample sizes generated from three distributions represented by Bivariate normal distribution, Bivariate contaminated normal distribution, and the Bivariate Exponential distribution.