Dear Fergus,
the simplest way to analyze the twin pairs is to calculate difference images
between twin and co-twin. These intra-pair differences can be now compared
between discordant monozygotic and dizygotic twins (genetic effect) and
between discordant and control monozygotic twins (disease effect). The
concordant twins can be used to test the effect of genetic liability. See
the paper of T.D. Cannon:
http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pubmed&pubmedid=11867725
The advantage of using intra-pair differences is that you remove the
variance between the twin and co-twin and only incorporate variance between
twins (intra-pair vs. inter-pair variance). This is maybe the same idea
like a random effects (or second level) analysis of fMRI data where you
remove the intra-subject variance (intra-subject vs. inter-subject variance).
One problem of using intra-pair differences is the order/direction of the
difference. For the discordant twins this is clear, for the concordant and
control twins one suggestion is to use birth order. However, the
order/direction issue is also occurring if you you don't use intra-pair
differences but the single data in a more fancy factorial model (as Ged
proposed).
Best regards,
Christian
____________________________________________________________________________
Christian Gaser, Ph.D.
Assistant Professor of Computational Neuroscience
Department of Psychiatry
Friedrich-Schiller-University of Jena
Philosophenweg 3, D-07743 Jena, Germany
Tel: ++49-3641-935805 Fax: ++49-3641-935280
e-mail: [log in to unmask]
http://dbm.neuro.uni-jena.de
On Tue, 2 Oct 2007 16:12:51 +0100, Fergus Kane <[log in to unmask]> wrote:
>Dear All,
>
>This question has been asked once before but went unanswered. I am
>analysing twin pairs discordant (one has one has not a diagnosis) and
>concordant (both have) for a psychiatric disorder - as well as control
>pairs. The sample is - mixed identical and non identical.
>
>The problem is: most statistical tests assume independence of observation,
>but twins are clearly not independent. Depending on the model, this results
>in a violation of such assumptions between and within groups. I'd like to
>know if there is any way of addressing this issue within SPM?
>
>Many Thanks
>
>Fergus
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