Monte Carlo Randomization

Monte Carlo randomization is one way to quantitatively evaluate observed data and test statistics.

In general, Monte Carlo Randomization (MCR) procedures follow this sequence:

1. Following the calculation of a statistic from the original dataset, observations are randomized (how many times?).

2. The statistic is recalculated for the randomized data.

3. Steps 1-2 are repeated a given number of times, amassing distributions that will be used to calculate p-values for the observed statistic.

4. P-values are calculated by comparing the observed statistic to the reference distribution.