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The purpose of the present study is to compare the efficiency of test statistics in testing the differences between two dependent datasets applying a regression framework with centered independent variable values. Comparisons of the efficiency of the test statistics, namely the t RCM b * 0 , the Wilcoxon matched-pairs signed-ranks test, and the Paired sample t-test, are made with the correlation coefficients, the sample sizes, and the ratio of mean different between the two datasets being varied. Simulations of the test statistics apply a Monte Carlo technique and are repeated 1,000 times. The research results show that the efficiency in controlling Type I errors of the Wilcoxon matched-pairs signed-ranks test and the Paired t-test is high under all scenarios, while that of the t RCM b * 0 is high only in case the r xy is not excessively high, that is, under 0.80. In contrast, the power of the test of the latter is significantly higher than the former under all scenarios.
Unchalee Tonggumnead (Thu,) studied this question.