Posted by
Arthur Kramer on
Jan 09, 2007; 9:39pm
URL: http://spssx-discussion.165.s1.nabble.com/Treating-Ordinal-Data-as-Continuous-tp1073024p1073032.html
Ordinal data may tend to act like interval when, (I believe) like you state,
when several items used to define a construct are summed, averaged, and
correlated to allude to an underlying factor. The resultant items, after
factor analyzing the larger set and elimination of those items with low
inter-correlations, can be said to operationally define the scale construct.
These may then be collapsed to provide a measure of the construct.
Unfortunately, oftentimes in the social sciences the methodologies neglect
the important steps of factoring out the underlying concept-as a matter of
fact, there is frequently only one (poorly constructed??) statement to used
to "operationally define" the construct in question; and this item is then
incorrectly referred to as a "Likert scale", totally disregarding the steps
Likert outlined in scale construction because it is a laborious process.
Maybe, if you took many different cheeses and extracted the primary
component(s) of the cheese (butter fat??), you could use some of that in you
recipe-but that would depend on whether it's goat milk cheese, sheep milk
cheese, or cow milk cheese, I guess.
Arthur Kramer
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of
Laurie Petch
Sent: Tuesday, January 09, 2007 5:01 AM
To:
[hidden email]
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)