Whenever multiple comparisons were made within one experiment, the significance level of P<0.05 was divided by the number of comparisons made; this maintained an experiment-wide error rate of 5% (Bonferroni-correction).
The number of conditions tested strongly reduced the number of samples we could use, as we wanted to maintain an experiment of a reasonable duration.
In all statistical comparisons, significance was assessed at p < 0.05, but in cases where multiple comparisons were made, we adjusted p-values using a sequential Bonferroni adjustment to maintain an experiment wide error rate of α = 0.05.
Multiple comparisons between the factor-level means were made using the Tukey honest significant difference (HSD) adjustment of comparison-wise p-values to maintain an experiment-wise cut-off p-value of 0.05.
Means in the same column, for a given factor, indicated by the same letter a, b, or c (for the stocking factor) and s and t (for the genetic rating factor) are not significantly different from each other at p = 0.05 using the Tukey honest significant difference p-value adjustment for multiple comparisons to maintain an experiment-wise error p-value of 0.05.
Bonferroni adjustment was used to maintain an experiment-wise α = 0.05 with multiple comparisons, such that αa = 0.002.
For specific comparisons (hypothesis tests) between treatments, Bonferroni correction (Bland, 2000) was used to maintain an experiment-wise probability for significance of 0.05.
For analysis of each outcome, the Bonferroni-Holm method of adjustment for multiple comparisons was applied to maintain an experiment-wise significance level of 0.05.
We correct the level of significance if multiple comparisons are made by dividing the P level of 0.05 by the number of comparisons made (Bonferroni-correction) to maintain an experiment-wide error rate at 5%.
When multiple tests are performed within one experiment, we correct the significance level by dividing the P value of 0.05 according to the number of comparisons made (Bonferroni-correction) to maintain an experiment-wide error rate at 5%; if, for example, 3 such comparisons are made, P < 0.05/3 is applied.
Where applicable, we divide this significance level by the number of single-group comparisons to maintain an experiment-wide error rate of 5% despite multiple comparisons (Bonferroni correction); if, for example, 20 single-group comparisons are performed (Experiment 1), we present P levels as P <.05/20 (i.e.,.0025).
