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The models incorporated CpG sites that were differentially methylated at the 0.001 significance level as assessed by the random variance t-test [23].
The models incorporated genes that were differentially methylated between tumor and surrounding tissue at the 0.001 significance level, as assessed by the random variance t-test.
Significant differential genes among the three groups were filtered by ANOVA and corrected by the random variance model (RVM [ 8].
These algorithms incorporate genes differentially expressed among different classes as assessed by the random variance t-test.
The models incorporated genes that were differentially expressed among genes at the 0.01 significance level as assessed by the random variance t-test [ 13].
To accurately estimate the per-group gene expression value, differentially expressed probe sets from different germination phases were filtered by ANOVA and corrected by the random variance model (RVM) [ 69- 71].
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Consequently, we obtained results with more power and less variation by using the random variance model corrected standard t-test or ANOVA methodology [ 8].
We estimated the random variance component by iteratively reweighted least squares (Berkey et al. 1995).
These increases were of the anticipated magnitude and direction, given the random variance introduced by differing levels of efficacy, compliance, and dosage among treated individuals.
We derived pooled random-effects estimates with the random variance component estimated by iteratively reweighted least squares (Berkey et al. 1995).
The random variance can be reduced by taking an average of surveys — and if pollsters have a persistent tendency to favor one candidate over another, we can account for that with our house effects adjustment, which is designed to detect and counteract these tendencies.
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