Posted by
Beadle, ViAnn on
Jan 09, 2007; 10:21pm
URL: http://spssx-discussion.165.s1.nabble.com/Treating-Ordinal-Data-as-Continuous-tp1073024p1073029.html
The number of tools for handling ordinal data are getting richer all the time. As an example, SPSS provides the PLUM procedure which from the can be accessed under Anayze>Regression>Ordinal... in 15.0 base SPSS. In earlier versions it was available as an option.
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of Bob Schacht
Sent: Tuesday, January 09, 2007 1:54 PM
To:
[hidden email]
Subject: Re: Treating Ordinal Data as Continuous
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