Posted by
Swank, Paul R on
Jan 09, 2007; 9:00pm
URL: http://spssx-discussion.165.s1.nabble.com/Treating-Ordinal-Data-as-Continuous-tp1073024p1073033.html
IRT is certainly one way in which we may be able to create more interval
measures. However, scales developed under classical theories may not
meet assumptions for IRT so it is not always possible to rescale an
already existing measure that was not developed from an IRT perspective.
Whenever I have compared scales developed by IRT to the same scale
scored in a more traditional way, there is usually a strong relation
between the two, especially when you are not close to the extremes. In
fact, my reason for liking IRT scales is the increased variance in the
extremes relative to classically derived scales. But I think many
clasically derived scales can be analyzed using ordinary parametric
procedures without too much loss of accuracy. I certainly would not like
to go back to the early 1950s when everyone was jumping from the
parametric ship onto the nonparametric one. Too limiting.
Paul R. Swank, Ph.D. Professor
Director of Reseach
Children's Learning Institute
University of Texas Health Science Center-Houston
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of
Dates, Brian
Sent: Tuesday, January 09, 2007 2:37 PM
To:
[hidden email]
Subject: Re: Treating Ordinal Data as Continuous
Bob's comments summon some of the reason that I became interested in IRT
as a way of looking at ordinal measures from an interval perspective.
One of the options is to examine using IRT to develop interval data and
then analyze that.
Brian
> At 07:00 AM 1/9/2007, Swank, Paul R wrote:
> >The problem is compounded when one thinks of measurement scales as
> >all or none, it's either ordinal or interval. However, win, place,
> >and show in a horse race is clearly more ordinal that IQ scores. For
> >IQ scores, it is clear that the difference between an IQ of 50 and an
> >IQ of 75 is perhaps greater than th difference between 75 and 100. On
> >the other and, the difference between an IQ of 100 and 101 is
> >probably pretty similar to the difference between 99 and 100. It all
> >relies on the relation between the scale values and the underlying
> >construct. I think some scales are closer to being interval than
> >ordianl while for others, the opposite is true. A lot has to do with
> >how well the scale was constructed.
>
> My main concern with this issue comes from satisfaction and importance
> scales. It seems to me that we don't have enough tools regarding
> ordinal measures. The analytical tool set for interval data is far
> richer than what is available for ordinal data. The median can be
> substituted for the mean, but there is no analytical equivalent of
> variance, even though it makes intuitive sense that an ordinal scale
> with results congregating at the extremes ought to be more 'variable'
> than a scale in which the results congregate around the median.
>
> Bob Schacht
>
> Robert M. Schacht, Ph.D. <
[hidden email]> Pacific Basin
> Rehabilitation Research & Training Center
> 1268 Young Street, Suite #204
> Research Center, University of Hawaii
> Honolulu, HI 96814
>
>
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