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BOOST is computationally efficient and detects statistical significant interactions based on approximated likelihood ratio statistic.
An overall significance estimate for the likelihood ratio statistic was obtained using the method for combining X2 statistics [ 33].
The values of the likelihood ratio statistic calculated from these datasets form the null distribution for statistical testing.
The promising zone approach uses the likelihood ratio statistic with the unadjusted value and other constraints.
A good compromise statistic for both kinds of alternatives is the likelihood ratio statistic.
c D is the likelihood ratio statistic, and P is the significance level.
d D is the likelihood ratio statistic, and P is the significance level.
At the same time, another empirical log likelihood ratio statistic is proposed based on an existing estimating equation and the limiting distribution of the empirical likelihood ratio statistic is shown to be a sum of weighted chi-square distributions.
One can employ the likelihood ratio statistic to test the superiority of the KwTP distribution over the other distributions.
Based on the theoretical asymptotic behaviour of the empirical likelihood ratio statistic, we propose, for a fixed design, a simpler test statistic, easier to use in practice.
The dual test method requires both the likelihood ratio statistic and the weighted statistic to be greater than the unadjusted critical value.
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CEO of Professional Science Editing for Scientists @ prosciediting.com