Smaller p-values can indicate statistical significance - but this is very
different from clinical significance!
For instance, if I have an intervention for obese people, and I've run a
well-designed RCT and found evidence for a tiny reduction in BMI in favour
of the intervention - but with a p-value of 0.01 - I would conclude that the
difference is *statistically* significant.
In order to find out whether this finding is *clinically* significant, I'd
want to find out whether there is any evidence that such a small reduction
in BMI is going to have a clinically meaningful effect on participants'
health - is it enough to reduce their risk of diabetes? CHD? Other
If you are writing up any research, it's a good idea to distinguish between
clinical and statistical significance.
From: Evidence based health (EBH)
[mailto:[log in to unmask]] On Behalf Of Anoop
Sent: 08 January 2011 16:33
To: [log in to unmask]
Subject: Re: P - Values
Thanks for the detailed response.
I understand that with smaller p-values you can look to see if it is
clinically significant, but how do we know if this clinically significant
difference is near to the true effect. It could be more than our clinically
significant value or less. ( which we can only find from CI). Makes sense?
In the exercise science field, studies still use the p-value concept.