Your English writing platform
Discover LudwigSuggestions(5)
Exact(60)
The resulting statistical maps were thresholded at p < 0.05 corrected for multiple comparisons at a cluster level.
The resulting p values were corrected for multiple comparisons at each phylogenetic level using the Benjamini-Hochberg correction (FDR).
The statistical maps of each group comparison were thresholded at p < .05 corrected for multiple comparisons at a cluster level using the threshold-free cluster enhancement (TFCE) option [32].
To investigate group effects, ANCOVA was used (age, gender, site and brain volume as nuisance covariates; results were FDR corrected for multiple comparisons at threshold of 0.05. We found volume reductions of the anterior, central, lateral dorsal (all FDR p<0.05) and a trend in the lateral posterior nucleus (FDR p<0.1) in migraineurs compared to controls.
Unless otherwise stated, activations were significant at p<0.05 corrected family-wise for multiple comparisons at the whole brain level.
We used a family wise error (FWE) correction at p<0.05 for multiple comparisons at a cluster level as the threshold for statistical significance for between-group comparisons.
Clusters with at least 15 voxels (400 mm3) and pcorr <0.05, corrected for multiple comparisons at the cluster level, were considered significant in group analyses of brain activation.
But these findings did not hold up using Bonferroni correction for multiple comparisons at a significance level of 0.05 (p-value threshold = 0.05/23 = 0.0022).
But this did not hold up using Bonferroni correction for multiple comparisons at a significance level of 0.05 (p-value threshold = 0.05/23 = 0.0022).
Group maps for each contrast were thresholded individually at z = 2.3 (corrected for multiple comparisons at the whole-brain level), binarized, and multiplied, which resulted in a map containing brain regions shared by spaced learning, repetition suppression, and subsequent memory.
This procedure found that contiguous clusters including seven or more voxels (> = 189 mm3) showing two significant effects each at p<.025 were corrected for multiple comparisons at an alpha level of.05.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com