On 15 Oct 2001 07:44:33 -0700, [EMAIL PROTECTED] (Warren) wrote:
Dear group,
It seems to me that the one issue here is that when we
measure something, then that measure should have some
meaning that is relevant to the study hypotheses.
And that meaning should be interpretable so that the
In article [EMAIL PROTECTED],
dennis roberts [EMAIL PROTECTED] wrote:
At 03:45 PM 10/9/01 -0400, Wuensch, Karl L wrote:
Some of those who think that estimation of the size of effects is more
important than the testing of a nil hypothesis of no effect argue that we
would be better served by
At 03:45 PM 10/9/01 -0400, Wuensch, Karl L wrote:
Some of those who think that estimation of the size of effects is more
important than the testing of a nil hypothesis of no effect argue that we
would be better served by reporting a confidence interval for the size of
the effect. Such
Title: RE: Standardized Confidence Intervals
Dennis..yes, the effect size index may be arbitrary, but for argument sake, say I have a measure of 'self-esteem', a 10 item measure (each item a 5-pt. Likert scale) that has a range of 10-50; sample1 has a 95% CI of [23, 27] whereas
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-Original Message-
From: dennis roberts [mailto:[EMAIL PROTECTED]mailto:[EMAIL PROTECTED]]
Sent: Tuesday, October 09, 2001 1:52 PM
To: Wuensch, Karl L; edstat (E-mail)
Subject: Re: Standardized Confidence Intervals
dennis roberts, penn state university
educational
At 03:04 PM 10/9/01 -0700, Dale Glaser wrote:
It would seem that by standardizing the CI, as Karl suggests, then we
may be able to get a better grasp of the dimensions of error...at
least I know the differences between .25 SD vs. 1.00 SD in terms of magnitude
well, yes, 1 sd means
