Sentence examples for multiple tests which from inspiring English sources

We conducted multiple tests, which may have increased the likelihood of chance findings, but considered adjusting for multiple testing not appropriate.

Likewise, our procedure for adding covariates to the augmented model toward arriving at the final model involves multiple tests, which could potentially introduce spurious findings.

All of the aforementioned methods assume statistical independence of the multiple tests, which can be violated when tests exhibit strong correlations (as mentioned above); furthermore, q-values imply subsequent validation in an independent sample, which may not occur.

The significance level was originally set at 0.05 and then subjected to a Holm's sequential Bonferroni adjustment as multiple tests which are indicated at the bottom of the relevant table.

The adjusted P value (called p_adj_Marker in TASSEL), is the site-wise P value adjusted for multiple tests which takes into account the dependence between SNPs due to linkage disequilibrium.

Both these values were significantly lower than a neutral dN/dS of 1 (P > 0.0001, likelihood ratio test, Bonferroni correction for multiple tests), which indicated that these genes were probably evolving under long-term purifying selection.

Although the data presented here are not robust, all our patients underwent the multiple testing, which is essentially time consuming.

However, the result for rs884861 is not significant with Bonferroni correction for multiple testing which gives a corrected p-value threshold of 0.0042.

Given the number of inserts (total 42) and discarding false positives, raw p-values were adjusted for multiple testing, which resulted in only a single insert position with significant difference and a p-value <0.01 (Adj. p).

The resulting p-values were subjected to Bonferroni correction and the significance threshold was set at p<0.05, although the multiple testing which arises from the pair-wise comparisons was not taken into account.

Correlation analyses between groups of genes (e.g. AMPs) and single factors (e.g. bacterial growth, transcription factor activity) usually included multiple testing, which has been taken into account by using a Bonferroni adjustment of the p-values.