[comp.ai] Twin Studies: Problems of Confounding Variables and Sample Populations

gilbert@cs.glasgow.ac.uk (Gilbert Cockton) (05/20/88)

In article <2865@cvl.umd.edu> harwood@cvl.UUCP (David Harwood) writes:
>	Can you substantially prove that there is not sound research
>which shows comparatively significant psychological similarity of
>identical twins, even when growing up apart?

To start, yes there are similarities.  The results weren't being
questioned, it was the interpretation, and the original 'experimental'
design.  These are the two major weak links in psychological research,
and for that matter in mathematical modelling (e.g. sociobiological
applications of game theory).

On experimental design, there is a problem in assuming that any population
of separated identical twins share all the variation likely in the
full population.  The role of adoption agencies is particularly
important, as they all have ideals of parenthood which many social
groups will not be able to fulfil. Hence the separated identical twins
will be less environmentally separated than the Bronx and the Berkshires.
Another problem in experimental design is the very measure of
'radically different environments'.   The twin studies cannot rely on
assuming that ANY difference in environment could be relevant to
development; the relationship has to be established by separate research.

It largely because of the uncritical approach to social environments
that any interpretations of 'results' will be invalid.  If you don't
control for confounding factors, your results aren't worth the paper
they're printed on.

I have no published work here either, but had to write on the topic as
part of my Education degree.  All the above is so obvious in
psychology that it wouldn't be worth publishing, except within a more
thorough review article.  I've bothered to post this to
	a) defend Richard's argument
	b) improve some people's awareness of experimental design
	   and thus hopefully encourage more constructive criticism
	   and less credulity about BIG twin studies.

Apologies to anyone who wants this sort of stuff out of comp.ai, but
if you are interested in computer simulation of human behaviour, I
don't see how you can justify the exclusion of anything to do with the
study of humanity from this group.
-- 
Gilbert Cockton, Department of Computing Science,  The University, Glasgow
	gilbert@uk.ac.glasgow.cs <europe>!ukc!glasgow!gilbert

	     The proper object of the study of humanity is humans, not machines