Great list of ways to refer to “close to, but not really, significant results.” Given how much P values can jump around using samples from the same population,my suggestion is to give the actual P value and talk about the effect size. No need to describe the P value itself.
What to do if your p-value is just over the arbitrary threshold for ‘significance’ of p=0.05?
You don’t need to play the significance testing game – there are better methods, like quoting the effect size with a confidence interval – but if you do, the rules are simple: the result is either significant or it isn’t.
So if your p-value remains stubbornly higher than 0.05, you should call it ‘non-significant’ and write it up as such. The problem for many authors is that this just isn’t the answer they were looking for: publishing so-called ‘negative results’ is harder than ‘positive results’.
The solution is to apply the time-honoured tactic of circumlocution to disguise the non-significant result as something more interesting. The following list is culled from peer-reviewed journal articles in which (a) the authors set themselves the threshold of 0.05 for significance, (b) failed to achieve that threshold value for…
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