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Fluctuating asymmetry and measurement error

1 message · Chris Longson

Chris Longson
# 
Hi Andrew,

Bear with me as it's a while since I did this and I was new to R at
the time, but lme is probably what you're after. Remember that you're
actually not all that interested in _individual_ variance, because FA
is a sample-level property.

You'll want to set up something like:

Treatment Individual Measure Result
1          1          1       foo
1          1          2       bar
1          2          1
1          2          2
2          3          1
2          3          2
2          4          1
2          4          2

Where result is absolute R-L, assuming you've done the checks for
size-dependence and so in. Then run an lme something like:

library(nlme)
test <- lme(Result ~ Treatment, random = list(Individual=~1))

Bearing in mind that you're not actually interested in the
individuals, you can either just include the multiple measures for each
individual and only worry about the remaining variance at the 'Treatment'
level, or you could do another model with 
"random = list(Measure=~1,Individual=~1)", then run:

anova(model1, model2)

This will tell you if the measurement term on its own is contributing
anything useful. In general it's better to have fewer factors, FA
analysis is low enough in power without cluttering it up.

Hope that helps. Now the R-gurus will probably tell you how you should
actually do the lme :)

Regards,
Chris