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Although there were twice as many nocturnal hypoglycemic excursions (Table 2) detected by CGM devices after resistance exercise (nine in total) versus aerobic exercise and no exercise (four for each), differences among conditions were not statistically significant.
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When more than two groups were compared, analysis of variance was used to evaluate significant differences among groups, and if significant differences were confirmed, each difference was further examined by Fisher's protected least significant difference method.
However, in SAVE each difference in variance across the groups takes up a dimension, and hence SAVE can have difficulty detecting mean differences and covariance differences.
For this analysis, we considered only the common populations, containing approximately 500 proteins for each difference set.
Such improved DE method is based on a classification which divides each difference into three categories: expandable, changeable and nonchangeable.
Finally, the mean value of each difference map was calculated.
We next assessed the degree of support for each alternative splicing choice for each Difference Region.
Such polynomials provided a means to estimate σ S, and hence, z values for each difference.
The values in the cells indicate the power to detect each difference for all four GRSs.
The variance for each difference in log RRs is estimated by the sum of their variances.
3. Sort the 120 likelihood differences, smallest differences first (each difference corresponds with a merge of two clusters).
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CEO of Professional Science Editing for Scientists @ prosciediting.com