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Sorry I meant to write: This doesn't mean that if you get a p value greater
than 0.05......
This doesn't mean that if you get a p value less than 0.05 the difference
between groups doesn't exist is just that you don't have high enough
confidence to report it.
If a difference exists between groups then with a large enough sample size
you will be able to bring the p value number below 5%.
----- Original Message -----
From: "Bryan Kirking"
To:
Sent: Wednesday, January 26, 2005 12:43 PM
Subject: Re: [BIOMCH-L] Stats Power. Report Confidence Limits - p values
> Recognizing that p-value interpretation is a topic that is hotly debated
> and further confused by subtle differences in terminology, I'd like to
pose
> the question:
>
> If "alpha, or type I error" is defined (as best as I know) as the
> probability of rejecting the null hypothesis when the null hypothesis is
true,
>
> And based on the associated p-value or confidence interval, one rejects
the
> null hypothesis, making the null untrue(?)
>
> Then doesn't alpha, or type I error become an impossibility (i.e, reject a
> true null when the p-value suggests the null is not true). I suspect the
> answer comes down to Dr. Greiner's remark that this is only one
experiment,
> but if we replicate the experiment 100 times wouldn't the same situation
be
> present? Does type II error (probability of not rejecting a false null)
> now become the best measure of confidence (and I use confidence for lack
of
> a better term)?
>
> As to predefining the alpha level, the issue becomes even more difficult
to
> me when I consider that most studies I read or perform usually have
> multiple comparisons. If one doesn't set overall confidence levels and
> therefore individual levels a priori, how do we guarantee that the overall
> confidence is maintained? Do we do analyses that "accepts" = 0.026 given
> that another variable is p=0.024 and therefore maintains 0.05? To me,
this
> is a very good reason for keeping with predefined values, as long as those
> values are suitable for your application.
>
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than 0.05......
This doesn't mean that if you get a p value less than 0.05 the difference
between groups doesn't exist is just that you don't have high enough
confidence to report it.
If a difference exists between groups then with a large enough sample size
you will be able to bring the p value number below 5%.
----- Original Message -----
From: "Bryan Kirking"
To:
Sent: Wednesday, January 26, 2005 12:43 PM
Subject: Re: [BIOMCH-L] Stats Power. Report Confidence Limits - p values
> Recognizing that p-value interpretation is a topic that is hotly debated
> and further confused by subtle differences in terminology, I'd like to
pose
> the question:
>
> If "alpha, or type I error" is defined (as best as I know) as the
> probability of rejecting the null hypothesis when the null hypothesis is
true,
>
> And based on the associated p-value or confidence interval, one rejects
the
> null hypothesis, making the null untrue(?)
>
> Then doesn't alpha, or type I error become an impossibility (i.e, reject a
> true null when the p-value suggests the null is not true). I suspect the
> answer comes down to Dr. Greiner's remark that this is only one
experiment,
> but if we replicate the experiment 100 times wouldn't the same situation
be
> present? Does type II error (probability of not rejecting a false null)
> now become the best measure of confidence (and I use confidence for lack
of
> a better term)?
>
> As to predefining the alpha level, the issue becomes even more difficult
to
> me when I consider that most studies I read or perform usually have
> multiple comparisons. If one doesn't set overall confidence levels and
> therefore individual levels a priori, how do we guarantee that the overall
> confidence is maintained? Do we do analyses that "accepts" = 0.026 given
> that another variable is p=0.024 and therefore maintains 0.05? To me,
this
> is a very good reason for keeping with predefined values, as long as those
> values are suitable for your application.
>
> -----------------------------------------------------------------
> To unsubscribe send SIGNOFF BIOMCH-L to LISTSERV@nic.surfnet.nl
> For information and archives: http://isb.ri.ccf.org/biomch-l
> -----------------------------------------------------------------
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