Okay, that does clarify things quite a bit for me. If I'm reading your
argument correctly, you're saying that the difference between the two
examples in the upper ends of the CIs (8.5415 versus .0782) does a
better job of illustrating the differences between the examples than
does the difference in effect sizes (.039 versus 4.25). Is that a fair
reading? (oh, and the p-value itself isn't really adding much of
anything, is it?).
Paul Smith
Karl L. Wuensch wrote:
Here are more details on the hypothesis test of no effect, which for the
sophisticated reader will provide the same information provided by the
confidence interval on d, but, IMHO, not for the naive reader (that is, most
consumers of and many producers of behavioral research).
A. n1 = 2, n2 = 2, t(2) = 4.25, p = .0512. Using the SPSS script at
http://core.ecu.edu/psyc/wuenschk/SPSS/CI-d-SPSS.zip or the SAS program at
http://core.ecu.edu/psyc/wuenschk/SAS/Conf-Interval-d2.sas , g (point
estimate of Cohen's d) = 4.25 and a 95% confidence interval on d runs
from -.0135 to 8.5415. Yes, I purposely chose a small sample size and a big
point estimate of effect, better to illustrate my point.
B. n1 = 5000, n2 = 5000, t(9998) = 1.95, p = .0512, g = .039, and the
confidence interval for d runs from -.0002 to .0782.
----- Original Message -----
From: "Paul Smith" <[EMAIL PROTECTED]>
To: "Teaching in the Psychological Sciences" <[email protected]>
Sent: Saturday, June 25, 2005 11:23 AM
Subject: Re: p = .051
Could you comment on how this comparison would look to you if instead of
just the p-value from the hypothesis test, you also included a measure
of effect size?
This is a very interesting discussion. Thanks,
Paul Smith
Karl L. Wuensch wrote:
My point is that the CI gives you everything you get with the hypothesis
test and more.
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