The phrase "a multiple test" is correct and usable in written English.
It can be used in contexts related to statistics, research, or assessments where multiple tests are being conducted or referenced.
Example: "In our study, we applied a multiple test to evaluate the effectiveness of the new treatment across various patient groups."
Alternatives: "a series of tests" or "multiple assessments".
A multiple test correction with Bonferroni procedure was performed.
A multiple test adjusting procedure, based on the rank-means paired differences, has been applied if the overall test was significant at the 0.05 level [32].
Therefore, we used the Bonferroni correction, respectively its exact version (the Sidak correction), both adjusting for the fact that the probability of a type I error in a multiple test differs from the error probability in a single test.
A multiple test adjusting procedure, based on the rank-means paired differences, showed statistical significance both in patients who worsened vs. those who remained on the same level (p = 0.011) but also vs. those who improved (p = 0.012).
The Kruskal-Wallis test revealed statistically significant differences among groups (p = 0.029), also confirmed by a multiple test adjusting procedure based on the rank-means paired differences (p = 0.018) (Table 2). Figure 1 Cephalalgiaphobia and frequency of migraine.
A multiple test adjusting procedure, based on the rank-means paired differences, showed that this statistical significance was attributable to the difference between 2nd vs. 1st group (p < 0.001) and 3rd vs. 1st (p < 0.001) but not to 3rd vs. 2nd group (Table 2).
Furthermore, a multiple testing analysis was not applied to genotypic differences in relation to various measures of kidney function.
However we were able to allow for this possibility without incurring a multiple testing penalty.
After considering a multiple testing correction (−log10 pFDR >3), no significant results were found for single-locus association tests.
A significant level of 0.05 was used with a multiple testing correction according to Benjamini and Hochberg [39].
When applying this method genome-wide, we applied a multiple testing correction with a FDR of <5%.
