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Mismatch rates were also incorporated in the variant detection model to dynamically adjust error rates based on local sequencing errors.
At this point the Bonferroni correction was also used to adjust the error rate.
An overall experiment-wise alpha of 0.05 will be used, with a Dunn/Bonferroni correction to adjust the error rate for individual analyses.
Here, we used a Fisher's exact test (with a Monte Carlo False Discovery Rate simulation; adjusted family-wise error rate α = 0.05) to determine the most common functions and pathways of each network.
We used the maximum of the clonal control derived error and the square of the ORP mismatch rate at a particular base as the adjusted position-dependent error rate for binomial error model p = max ε, δ 2 P-value = 0.01 with Bonferroni correction was used as the significance threshold for each hypothesis test.
A Bonferroni adjusted type I error rate of 2.5% for a double-two-sided t test with 80% power was used, and 36 patients were required for each arm under the more strict assumptions of the HP BMD expected differences (total 72) and 30 under the LS assumptions (total 60).
The sequences were assembled iteratively, adjusting the assumed error rate incrementally between 0% and 6%.
We took into account the possibly differing type I error rates of the tests and we estimated powers adjusted for type I error rate [ 35].
When selection of trials was modeled by trial size and treatment effect magnitude, the power adjusted for type I error rate increased when the true average odds ratios moved away from 1.
Across all scenarios, visual inspection of the trellis graphs showed that the power adjusted for type I error rate increased with increasing number of meta-analyses and trials per meta-analysis and with decreased between-trial variance within a meta-analysis.
miR-132 qRT-PCR expression across nuclei at LD + T 3D, 7D, 21D, and LDW relative to SD were fit with ANOVA and had p-values adjusted using a family-wise error rate (FWER) adjustment and subsequent Hommel correction for multiple comparison.
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