Exact(9)
Based on the corrected data, we can conduct association tests correcting for population stratification.
We analyzed categorical variables using Pearson chi-squared tests correcting for the cluster sampling design of the EBF-trial.
For data involving two or more independent variables, two-way ANOVA was used, and Bonferroni post hoc tests, correcting for multiple comparisons, were used.
Post hoc tests (correcting for multiple comparisons with the Tukey-Kramer method) were performed in order to investigate the source of the significant Condition × Distance interactions.
Pairwise comparisons were developed using 'Tukey' tests, correcting for multiple comparisons by the 'single-step' method using Multcomp package (Hothorn et al. 2008).
As population structure can artificially produce statistically significant isolation by distance relationships, we also conducted partial Mantel tests correcting for the influence of habitat.
Similar(51)
We used two-tailed, independent samples t-tests (corrected for multiple comparisons using Scheffe's F test), and Mann-Whitney U tests (corrected for multiple comparisons using Bonferroni correction) in order to evaluate differences between means.
No figurative-operative (imperceptible-perceptible) condition pairs showed significant difference in these parameters (post hoc t tests, corrected for multiple comparisons; see Supplementary Table 2).
Testing was performed using Friedman ANOVA and subsequent Wilcoxon tests, corrected for multiple comparisons.
The most stringent threshold was 5.10-6 5.10-6 corresponds to approximately 10 000 independent tests corrected whichBonferroni.
P values were derived from multiple tests corrected in order to reduce false-positive rates.
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