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
would be useful to present confidence intervals in standardized
units." This suggestion was not well received by this group. Others have,
however, made what appears to be the same suggestion.
While reviewing the materials on the reading list for my stats class this
afternoon, I came across the
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 width
of the CI does have meaning...why would you want to estimate
the
e that we
>>would be better served by reporting a confidence interval for the size of
>>the effect. Such confidence intervals are, in my experience, most often
>>reported in terms of the original unit of measure for the variable involved.
>>When the unit of measure is arbitrary
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 ab
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>-Original Message-
>From: dennis roberts [<mailto:[EMAIL PROTECTED]>mailto:[EMAIL PROTECTED]]
&g
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]
ffect. Such confidence intervals are, in my experience, most often
>reported in terms of the original unit of measure for the variable involved.
>When the unit of measure is arbitrary, those who are interested in
>estimating the size of effects suggest that we do so with standardized
>es
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 confidence intervals are, in my experience, most often
In article <9p2d8l$clk$[EMAIL PROTECTED]>,
Ronald Bloom <[EMAIL PROTECTED]> wrote:
>Herman Rubin <[EMAIL PROTECTED]> wrote:
>> Teaching people to use something without any understanding
>> can only be ritual; this is what most uses of statistics
>> are these days.
>> If one does not use numbe
l R. Swank <[EMAIL PROTECTED]> wrote:
> >I use to find that students respoded well to the idea that the hypothesis
> >test told you, within the limits of likelihood set, where the parameter
> >wasn't while confidence intervals told you where the parameter was.
>
> >P
Herman Rubin <[EMAIL PROTECTED]> wrote:
> Teaching people to use something without any understanding
> can only be ritual; this is what most uses of statistics
> are these days.
> If one does not use numbers, it is opinion. I hope that the
> pediatricians you have in your classes do not misus
In article <001501c1482f$756d6190$e10e6a81@PEDUCT225>,
<[EMAIL PROTECTED]> wrote:
#If your purpose is to try and teach students about confidence intervals,
#then it makes little sense to start out by telling them the
#counterexamples.
Why not? My purpose would be to teach s
In article <001501c1482f$756d6190$e10e6a81@PEDUCT225>,
Paul R. Swank <[EMAIL PROTECTED]> wrote:
>If your purpose is to try and teach students about confidence intervals,
>then it makes little sense to start out by telling them the counterexamples.
Without counterexamples
In article <008201c14763$9392f260$e10e6a81@PEDUCT225>,
Paul R. Swank <[EMAIL PROTECTED]> wrote:
>I use to find that students respoded well to the idea that the hypothesis
>test told you, within the limits of likelihood set, where the parameter
>wasn't while confidence in
If your purpose is to try and teach students about confidence intervals,
then it makes little sense to start out by telling them the counterexamples.
I don't start telling students about standard deviations by describing a
Cauchy distribution. Now if we are going to do away with confi
half Of Bill Jefferys
#Sent: Thursday, September 27, 2001 11:31 AM
#To: [EMAIL PROTECTED]
#Subject: Re: Confidence intervals
#
#
#In article <008201c14763$9392f260$e10e6a81@PEDUCT225>,
#<[EMAIL PROTECTED]> wrote:
#
##I use to find that students respoded well to the idea that the hypothesis
##t
PROTECTED]]On Behalf Of Bill Jefferys
Sent: Thursday, September 27, 2001 11:31 AM
To: [EMAIL PROTECTED]
Subject: Re: Confidence intervals
In article <008201c14763$9392f260$e10e6a81@PEDUCT225>,
<[EMAIL PROTECTED]> wrote:
#I use to find that students respoded well to the idea that the hypo
In article <008201c14763$9392f260$e10e6a81@PEDUCT225>,
<[EMAIL PROTECTED]> wrote:
#I use to find that students respoded well to the idea that the hypothesis
#test told you, within the limits of likelihood set, where the parameter
#wasn't while confidence intervals told you wh
I use to find that students respoded well to the idea that the hypothesis
test told you, within the limits of likelihood set, where the parameter
wasn't while confidence intervals told you where the parameter was.
Paul R. Swank, Ph.D.
Professor
Developmental Pediatrics
UT Houston Health Sc
I do have a binary response with 3 treatments groups. I want to do all
pairwise comparisons by presenting the confidence intervals for the risk
difference and relative risk. However, I should correct for multiple testing
and it should be something less conservative than the Bonferroni correction
Neeraj,
It is easy to verify that if Y is exponential with mean t then Y/t is is
exponential with mean 1.
Also, the sum of n exponentials with parameter 1 has the distribution
Gamma(n,1). Most texts on probability and statistics (Feller Vol II, Mood
and Graybill) are references. It is a consequ
I am looking through notes for confidence interval for the exponential
mean.
I have been given that:
Suppose Y_1,...,Y_n ~ Exp(t^(-1)) independently. Then for each of the
Y_i:
f(y_i|t) = t^(-1) exp(-y_i/t).
We are then finding the maximum likelihood estimator ^t^, and with
various calculation
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