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View Full Version : FW: [BIOMCH-L] Stats Power. Report Confidence Limits - p values



gchalmers50
01-26-2005, 05:34 AM
An interesting review of the history of the p-value, and its potential
role today can be found in a BMJ article freely available at:

http://bmj.com/cgi/reprint/322/7280/226

Sifting the evidence-what's wrong with significance tests?
Jonathan A C Sterne, George Davey Smith

In the introduction it states: "In this paper we consider how the
practice of significance testing emerged; an arbitrary division of
results as "significant" or "non-significant" (according to the commonly
used threshold of P=0.05) was not the intention of the founders of
statistical inference. P values need to be much smaller than 0.05 before
they can be considered to provide strong evidence against the null
hypothesis; this implies that more powerful studies are needed.
Reporting of medical research should continue to move from the idea that
results are significant or non-significant to the interpretation of
findings in the context of the type of study and other available
evidence."


************************************************** ******************
Gordon Chalmers, Ph.D.
Dept. of Physical Education, Health and Recreation
Western Washington University
516 High St.
Bellingham, WA, U.S.A.
98225-9067
http://www.ac.wwu.edu/~chalmers/
Phone: 360-650-3113
Email: Gordon-dot-Chalmers-at-wwu-dot-edu
in above email address: replace "-dot-" with "."
replace "-at-" with "@"


-----Original Message-----
From: * Biomechanics and Movement Science listserver
[mailto:BIOMCH-L@NIC.SURFNET.NL] On Behalf Of Bryan Kirking
Sent: Tuesday, January 25, 2005 2:46 PM
To: BIOMCH-L@NIC.SURFNET.NL
Subject: Re: [BIOMCH-L] Stats Power. Report Confidence Limits - p values

To comment and question some of Dr. Allison's insight:

>>My understanding of the arbitrary "line in the sand" of 0.05 was
>>originally due to the choice of the original tables (pre computer)

I have heard this too. It was very tedious to calculate probabilities
(pre
Personal Computer) as is done now, so the investigator would pick the
appropriate values to simplify the calculations.

>>The p value reflects the probability of the observed change happening
by
chance.

Isn't this only correct if the null hypothesis is correct (not
rejected?). This is why (as explained to me by statisticians - I won't
claim authority here) it is considered incorrect to differentiate
"significant" from "very significant" from "highly significant"? I
present
this point because of your comment about relating the alpha level to the
seriousness of the outcome.



Bryan Kirking
ProbaSci LLC
tel. 512.218.3900
fax. 512.218.3972
www.probasci.com
bryan@probasci.com

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