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Thus, the risk of reporting erroneous results due to mass significance, problems with multi-co-linearity and bias in post-hoc analyses was reduced by conducting similar analyses with similar results in a new study.
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This approach, replicating the most interesting results of the pilot study, will address significance problem that may arise when dealing with a large set of parameters.
By testing for associations between time-course gene expression and the top two PCs, we avoid this challenging problem and consider instead the tractable association significance testing problem with a simple null hypothesis H 0 : γ i = 0 versus H 1 : γ i ≠ 0 (as opposed to a composite null).
The use of more than one primary outcome (co-primary outcomes) necessitates adjustments of the thresholds for significance because of problems with multiplicity [ 34].
Due to the small sample size and general problems with significance testing (Sterne and Davey Smith, 2001), we did not use tests for statistical significance.
Stuart method has problems with significance scoring.
Because of the problems with significance scores, we omitted the Stuart method.
In their article, Stang et al. [ 2] not only describe the problems with significance testing, but also allude to the solution, which is to rely on estimation using confidence intervals.
To present terminology-related problems with economic significance needs a rough division of this sector into its internal and external areas.
This assumes particular significance given the emergence of problems with habitat fragmentation and climate change.
These methods permit an evaluation of differences in variables without the risk of problems with mass significance and need for normal distribution of data or strict independence among variables as in conventional statistics.
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