Re: Treating Ordinal Data as Continuous

Posted by bdates on Jan 09, 2007; 8:37pm
URL: http://spssx-discussion.165.s1.nabble.com/Treating-Ordinal-Data-as-Continuous-tp1073024p1073034.html

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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