Monte Carlo Evaluation of Resampling-Based Hypothesis Tests

Abstract

Monte Carlo estimation of the power of tests that require resampling can be very computationally intensive. It is possible to reduce the size of the inner resampling loop as long as the resulting estimator of power can be corrected for bias. A simple linear extrapolation method is shown to perform well in correcting for bias and thus reduces computation time in Monte Carlo power studies.