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The strict p value cut-off we applied was carried forward when Q values were calculated.
A backwards elimination approach with a strict P < 0.01 inclusion criterion was then used to obtain an optimal subset of variables (a forwards selection approach yielded the same results).
In order to identify those potential behavioural mediators of preventive delivery (theoretically amenable to change), that were most strongly and independently associated with the preventive outcomes, multivariable linear regression models were run using a stepwise variable selection method with a strict p < 0.001 for model entry.
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To adjust for multiple testing we considered a more strict P-value (<0.005) as statistically significant.
We believe that the primary reason for such discrepancies is that strict p-values and other restrictive criteria are often utilized to generate gene lists.
Rather than simply limiting findings based on a strict p-value criterion, they recommend a careful evaluation of study results that focuses specifically on a well-defined question.
As the total number of predictors is fairly small, we judged that the risk of overfitting was minimal, and we used a less strict P-level for selection.
In order to restrict as much as possible our motif comparison, we chose a strict p-value equal to that successfully used to validate the motif comparison algorithm TOMTOM (see additional data file in [ 16]).
The only exception was the model with mutually adjusted latent PFASs (Additional file 1: Model 4, Additional file 1: Table S4) which did not satisfy the strict P-value criterion, but had acceptable values for the other fit-indices.
One limitation of our analysis is that we have only two biological replicates per condition, but we address this limitation in part by requiring relatively strict p-values and fold-change values in order for a gene to be considered significantly differentially expressed.
Since we were performing 16 different tests, we used a stricter p value for significance of 0.01.
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CEO of Professional Science Editing for Scientists @ prosciediting.com