Sentence examples for multiple testing studies from inspiring English sources

P-values are not corrected for multiple testing Studies in the sister species F. vesiculosus have shown that the inherited part of the variation in growth rate is low while it is high in phlorotannin content [ 25, 26], and this is similar to what we found for F. radicans.

Guidelines for achieving this cover three aspects of surrogates testing: experimental design of tests, ongoing corroboration assessment of evidence produced by tests, and accumulation of lessons learned from multiple test studies over time.

All analyses were considered exploratory, with statistical significance defined as P < 0.05 and no adjustment for multiple testing; the study was powered for the primary study outcome only.

Although there is the potential issue of multiple testing, this study is still a valid hypothesis generating study.

Although the association was not significant after correcting for multiple testing, this study is the first to report the evidence of association of rs11531690 with serum 25(OH D concentrations.

However, a consensus on how to correct such multiple testing on study combining brain imaging and genetics has not been reached in this research field.

We tested interactions with 19 SNPs in this study, and multiple testing is subject to false positives.

What is clear is that no associations replicate across studies, with significance levels often being marginal after correction for multiple testing, and several studies find no significant associations at all (Table 1).

First, due to the exploratory nature of this study, we chose not to correct for multiple testing; therefore, the study findings should be tested in a confirmatory study.

We chose to use a stepwise Bonferroni-type procedure for multiple testing since simulation studies have confirmed that such procedures generally perform as well or better than more complicated alternative procedures (Cribbie, 2017).

No consensus exists regarding the best method to correct for multiple testing in association studies.