A random permutation procedure recalculates a statistic many times by reshuffling the data values among the map units to generate a reference distribution.
The statistical significance of KST was calculated by permuting the sequences across the populations and recalculating the statistic 10,000 times to produce a null distribution.
To assess whether Tajima's D statistic (T ajima 1989) was significantly different from that expected under the standard neutral model, we produced a null distribution by recalculating the statistic from 1000 coalescent simulations conditional on the number of segregating sites observed in our data.
During randomisation, within each network, we randomly reassigned the strength values to all nodes without replacement and recalculated the test statistic.
Every time a participant changes residences the statistic is recalculated.
This statistic is recalculated for each case every time there is a change in place of residence.
The GEA results in a robust mean squared error (MSE), which replaces the current MSE from the classical ANOVA, a new F statistic is recalculated and a robust p value derived.
Therefore, self-reported health status was dichotomised in alternative ways: (i) excellent versus very good, good, fair or poor, (ii) excellent or very good versus good, fair or poor, (iii) excellent, very good or good versus fair or poor, and (iv) excellent, very good, good or fair versus poor, and the relative efficiency statistic was recalculated.
To estimate distributions for the test statistic, the spatial scan statistic uses the Monte Carlo method and assigns cases to individuals in the population randomly, and recalculates the test statistic.
The null distribution of each of these test statistics was determined by reassigning the metabolic rates to individuals at random without replacement (i.e., shuffling the metabolic rates) 1000 times, each time recalculating the test statistic.
Therefore, we fit a set of extended models allowing for a deviating effect of each study design in turn and recalculate the Q statistic.
