Hi

On Wed, 26 Feb 2003, Hatcher, Joe wrote:

>       I would argue that random assignment is only a means to
> an end, the end being having at least two groups that are
> assumed to be roughly equal on all variables.  Seen that way,
> a within-subjects design is simply another means of achieving
> the same end.  I understand the limitations, but would argue
> that with appropriate counter-balancing these can be
> overcome.  This may be an argument of convenience for me or a
> result of dissonance-reduction on my part; we have a very
> small subject pool and strongly encourage within-subject
> designs where possible

I would agree with Joe here.  Moreover, within-subject designs
are certainly the dominant design in many areas of psychology
that have a (perhaps undeserved according to Mike?) reputation as
being experimental (e.g., cognitive, perception, ...).  
Within-subject designs also generally increase the power of the
design/analysis, as the error term is usually smaller when
individual differences in subjects are reduced.

> > From:       Mike Scoles
> > I'm going to stick with Sir Fisher and reserve the term
> "experiment" for > situations where there is random
> assignment to conditions. I do not know > of > any
> within-subjects designs that would not be better as mixed
> designs. > Within-subject designs are too easily compromised
> by history, maturation, > instrumentation, attrition, and
> (sometimes) test sensitization and > regression issues.  
> Let's see, the only one of the "Big 7" that I left out > was
> subject selection--the major problem with quasi-experiments.  
> Of > course, > good quasi-experiments can provide information
> as useful as a marginal > experiment.

If you think of it as random assignment of conditions to subjects
(rather than the reverse) then within-subject designs can be
accommodated.  That is, it is possible make the conditions
orthogonal to many (all?) potentially confounded variables in
within-subject designs.  

I would also extend Mike's last statement even further.  
Non-experimental designs can also provide information as useful
as (or more useful than) marginal or poorly designed experiments.  
Many students appear to believe (wrongly, I think) that an
experiment necessarily means causal inferences are warranted,
whereas in fact only well-designed experiments permit strong
causal inferences.

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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