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Our first hypothesis (scenario 1) was that a pharmaceutical sponsor would favour its own drug in placebo controlled or active comparator trials of statins or the highest dose of its own drug.
Since this procedure generates a multiple hypothesis scenario where each group will have an individual p-value for each recombination test, users can choose to control the Type 1 errors through the false discovery rate (FDR), configuring POTION to further analyze only genes with corrected q-values smaller than user-defined cutoffs for all tests executed.
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The first four lines of Table 2 represent null hypothesis scenarios, with a risk ratio of 1.
In the section entitled "Model interrogation", we describe five scenarios, which are used to explore the values of the parameters that maintain genetic variation in worms (Scenarios 1 and 2), describe the properties of the worm infection and genotype by genotype interaction (Scenarios 3 and 4) and test the hypotheses (Scenario 5).
For the exploration of industry sponsorship bias, we had two a priori hypotheses (scenarios 1 and 2).
For the group-based hypotheses scenarios, we simulated 10 runs for each scenario, after which we selected the scenario(s) from each group with the highest posterior probability.
Similarly to the recombination analysis, this step is also a multiple hypothesis testing scenario, and therefore POTION also reports corrected q-values from the list of p-values obtained for all groups evaluated using a given nested model pair (q-values are calculated as explained for recombination detection).
We also tested the hypothesis that scenarios associated with worse outcome would result in different cytokine release patterns.
On the other hand, when encountering complex hypothesis testing scenarios in practical data analyses, resorting to resampling-based methods is a very natural and effective strategy.
The decision context IV aims to establish a strong hypothesis-driven scenario based on mechanistic reasoning with structural analogues, including at least one molecule with markedly different potency.
Finally, the simultaneous search for recombination and/or positive selection in several groups of homologs creates a multiple hypothesis-testing scenario that requires correct statistical treatment to control the frequency of Type 1 errors [ 8, 22].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com