Hi,

thanks a lot for all the replies!
I've been reading some of the recommended material, plus your posts and
indeed I can see that's a huge can of worms, with a lots disagreement...
somewhat frustrating for a new kid in the field, I'll admit.

about the Pearson's r in the effect size issue - I'm doing a meta-analysis
in which I'm using them as a measure of effect size. From what I've read,
and seems sensible, in case of complex designs with > 1 explanatory
variables, they should be calculated based on model statistics for the
effects of interest (So in the case I've described, I'm interested in r for
sz-malecat relationship and I'm trying to calculate it from the malecat t
value given by lmer. The equation which does it includes df number, hence my
need for it). If someone knows about other ways to calculate Pearson's r
from such models that would omit the controversial df-s, I'd be hugely
grateful to hear about it (haven't found anything myself though).

Zofia

-- 
--
Zofia Maria Prokop
PhD student
Molecular and Behavioral Ecology Group
Jagiellonian University
Gronostajowa 7
30-387 Krakow, Poland
zofia.prokop@uj.edu.pl

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