Hi
On Sat, 17 Mar 2001, Ben Kenward wrote:
> My girlfriend is researching teaching methods using a questionaire, and she
> has answers for questions in the form of numbers from 1 to 5 where 5 is
> strongly agree with a statement and 1 is strongly disagree. She is proposing
> to do a t-test to compare, for example, male and female responses to a
> particular question.
>
> I was surprised by this because I always thought that you needed at least
> interval data in order for a t-test to be valid. Her textbook actually says
> it is OK to do this though. I don't have any of my old (life-sciences) stats
> books with me, so I can't check what I used to do.
>
> So are the social scientists playing fast and loose with test validity, or
> is my memory playing up?
Once upon a time (and repeated at various intervals thereafter)
there was considerable debate about the relationship between
level of measurement (nominal, ordinal, interval, ratio) and type
of inferential statistics that were appropriate (allowed in some
cases). The standard story a la Stevens was pretty much what you
are remembering. However, a number of people criticized this
view and the accepted distinction now tends to be categorical
(nominal) vs. numerical (the rest). That is, any inferential
procedure (e.g., t) can in principle be used for any numerical
data. There are still dissenters, however, who agree with
Stevens. Do a google search (www.google.com) on "stevens levels
of measurement inferential" and you'll find mixed positions.
Best wishes
Jim
============================================================================
James M. Clark (204) 786-9757
Department of Psychology (204) 774-4134 Fax
University of Winnipeg 4L05D
Winnipeg, Manitoba R3B 2E9 [EMAIL PROTECTED]
CANADA http://www.uwinnipeg.ca/~clark
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