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Although in prior efforts26, authors compared temperature-corrected outputs of modules, we chose to apply no correction such that our results for SR accounted for both direct effects (radiation attenuation) and indirect effects (changes in the module's temperature) of the soiling.
We also iteratively tested each of the 27 autosomes for a global difference in expression from the remaining autosomes, applying a Bonferroni correction such that statistical significance occurred at P < 0.00179 = 0.05/28.
For regions with a high RPC (underconfidence), the sharpness has been improved by the RPC correction such that model probabilities are more dispersed from the climatological value and now sample more extreme values, and the Brier score has been improved (0.20 compared to 0.23 and 0.25 for the original model output and climatology, respectively).
We found a strong correlation between survival and gene activity that alters glycogen content (* P < 0.001 vs. control RNAi, one-way ANOVA with Dunnett's multiple comparison correction), such that 18 of the 33 GSG knockdowns displayed significant increases in survival relative to controls, and all seven of the GSG knockdowns that were tested displayed significant survival decreases.
We assessed significance using a 0.05 family-wide type I error rate under a Bonferroni correction, such that a term was considered significant if p ≤ 0.05 n C n O where n C is the number of clusters found and n O is the number of nodes in the ontology.
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The results shown above suggest that an easy thermal correction, such as that performed here, is necessary for detailed tsunami analyses.
Corrections such as that of the maximal pressure at the end of the inspiratory flow phase have been suggested.
Strict correction, such as Bonferroni correction that assumes independent multiple hypothesis testing, would be unnecessarily strict because we often see strong correlation in signals across time, frequencies and neighboring electrodes.
RAD loci and RAD alleles are initially described as candidates to indicate that further error correction (such as removal of repeats and RAD alleles appearing in only one individual) will take place downstream during processing.
Even if our sample dimension was rather large, nevertheless, we decided to use a continuity correction such as the Yates correction, considering that we were approximating a continuous χ distribution by discrete observations and that the 2 × 2 tables that we utilized only have one degree of freedom.
Note however, that an additional confounding factor is that these statistical tests do not make corrections for assessing multiple trees, nor is a simple multiple-test correction such as the Bonferroni correction applicable to the problem [78].
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