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Despite the fact that the drop in PTX rates is visually convincing during the intervention period, we tested six different intervention dates and statistically significant results may be due to chance by multiple testing (limited power precluded applying correction factors such as Bonferroni).
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* OR adjusted for age and gender † Reference groups are the homozygous wild genotypes for each gene ‡ Reference group is fast acetylators (homo-heterozygous for the wild-type allele) To reduce the chance of multiple testing, we limited the gene-gene interaction analyses to the three SNPs that exhibited the most prominent association with gastric cancer.
At least, we did not correct for multiple testing, which limits our results.
These conclusions are based on the exploratory data from a prospective study using two-sided statistical tests with no correction for multiple testing and are limited by the few deaths for the survival assessment and the lack of information regarding the timing of initiation of herbal remedy use or duration or frequency of, or reasons for herbal remedy use.
These conclusions are based on exploratory analyses of data from a prospective study using two-sided statistical tests with no correction for multiple testing and are limited by few deaths for mortality analysis and lack of information on when herbal remedy use was initiated or duration of or reasons for use.
The Bonferroni correction widely applied to human GWA analyses imposes a substantial multiple testing penalty, effectively limiting the ability to detect loci with small effects to reduce the detection of spurious loci.
It also helps prioritize tests of gene-gene interaction, which can limit multiple testing issues.
To limit multiple testing in the replication cohort, we only examined SNPs that displayed associations in the discovery cohort.
Thus, it allows a synthetic presentation of results while improving precision, reducing the number of tests and limiting multiple testing difficulties.
For categorical variables, we limit multiple testing problems by reporting overall chi-square test results and then describing selected group proportions.
Data from the postvaccination surveys (CSS-1 3) CSS-1 3mbined to improve the statistical powereand to reducombinedumber of comparisons, toereby limprove multhele testatistical
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