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In order to determine the effects of multiple testing, these analyses were also conducted with all 17 chronobiological variables considered individually.
Finally, as we did not correct our interaction analyses for multiple testing, these findings should thus be interpreted with caution, as they are in need of replication.
After correction for multiple testing, these differences were no longer significant.
However after a Bonferroni correction for multiple testing these differences were no longer significant.
However, due to the very low number of co-infected infants and multiple testing, these findings must be interpreted with care.
However, after adjusting for multiple testing these associations were borderline with an adjusted P-trend=0.068 P-trend=0.068signiforantheNP (rs2854344).
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Normal: under 100 mg/dL Prediabetes: 100 to 125 mg/dL Diabetes: 126 or higher mg/dL 1There are multiple tests; these numbers are for the fasting plasma glucose test.
In addition to implementing multiple tests, these packages make it simple to consider different subsets of the data for analysis.
When software algorithms are used to generate a single result from the results of multiple tests, these algorithms are considered devices in and of themselves.
As there has been no adjustment for multiple testing, the results for these end points will have p-values that are too small.
There is an inevitable loss of statistical power when stratifying cases into clinical sub-types, and after adjusting for multiple testing, the most significant of these associations (P-trend = 0.008 for rs4988344) was P = 0.17.
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