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This informal process of multiple testing means that it is impossible to gauge the true significance (in a statistical sense) of an apparent disease excess in a particular locality.
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The p values were adjusted for multiple testing by means of the Holms procedure.
However, making some allowance for multiple testing would means that the P-value of 0.035 for p53 immunostaining is of borderline statistical significance.
The p-values for the coefficients of interest were adjusted for multiple testing by means of Benjamini and Hochberg's algorithm [ 31], which controls the expected false discovery rate (FDR) below the specified value.
It is important to avoid over-interpretation of the results of the meta-regression analyses we conducted due to their observational nature, limited statistical power and multiple tests, which meant heightened probability of type I (obtaining a false positive result) and type II (obtaining a false negative result) errors.
This is followed by multiple testing adjustments, and mean levels of methylations were compared across phenotype categories while adjusting for the known and computed confounders in the form of PCs.
Adjustment for multiple testing is done by means of the Bonferroni Holm method [ 8].
An α-adjustment (0.05) for multiple testing was performed by means of the Holm procedure, a more powerful approach than the Bonferroni procedure.
Because of multiple testing for the estimated marginal means, a significance level of p < 0.01 was applied.
Seven separate control cell lines underwent multiple testing to calculate control data (mean ± SD; n = 7), patient fibroblasts were tested multiple times as indicated in Fig. 4.
Similarly, while we consider CHAMBER to be an exploratory algorithm, the use of P-values may require correction for multiple testing by a variety of standard means [37].
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