Monte Carlo evaluation of resampling-based hypothesis tests

What is it about?

Monte Carlo evaluation of resampling-based tests is often conducted in statistical analysis. However, this procedure is generally computationally intensive. In this article, we propose a novel Monte Carlo evaluation procedure. Theorems as well as simulations show that the proposed method can give smaller or comparable root mean squared errors and bias with much less computing time.

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Why is it important?

The proposed Monte Carlo evaluation procedure has much less computing time with smaller root mean squared errors, thus can be strongly recommended especially for evaluating highly computationally intensive hypothesis testing procedures in genetic epidemiology.

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