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Date:   Tue, 9 Jan 2007 11:00:43 -0600
Reply-To:   "Swank, Paul R" <Paul.R.Swank@uth.tmc.edu>
Sender:   "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:   "Swank, Paul R" <Paul.R.Swank@uth.tmc.edu>
Subject:   Re: Treating Ordinal Data as Continuous
Comments:   To: Laurie Petch <lauriepetch@sasktel.net>
Content-Type:   text/plain; charset="us-ascii"

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.

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:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Laurie Petch Sent: Tuesday, January 09, 2007 4:01 AM To: SPSSX-L@LISTSERV.UGA.EDU Subject: Treating Ordinal Data as Continuous

Apologies, this is more of a statistical question, though it does have an indirect bearing on SPSS. As subscribers to this list will know, in psychology it is common practice to treat ordinal level data deriving from rating scales as if they were continuous data and subjecting them to inferential statistical analysis. The argument I have heard in favour of doing this is that ordinal data behave much more like continuous data when they are summed and averaged. I have not seen this argument in writing, however, and would be grateful to anyone who can point me in the direction of a relevant source.

Also, if anyone can suggest counter-arguments to this justification, that would be great too. It just strikes me that a score of '120' as opposed to '118' on an anxiety measure is data of a very different kind than someone who is 120cm tall as opposed to 118cm.

To say that ordinal data behave like continuous data is surely rather like saying that, since cheese 'behaves' more like butter when it is heated, it's okay to use cheese instead of butter to make a cake?

Laurie -------- Laurie Petch Chartered Educational Psychologist (British Psychological Society)


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