On Jun 20, 2010, at 1:38 PM, Ekaterina Pek wrote:
Hi, Ted.
Thanks for your reply. It helped. I have further a bit of questions.
It may be that lm(log(b) ~ log(a)) is, from a substantive point of
view,
a more appropriate model for whetever it is than lm(b ~ a). Or it may
not be. This is a separate question. Again, Spearman's rho is not
definitive.
How one determines if one linear model is more appropriate than
another ?
And : linear model "log(b) ~ log(a)" is okay ? I hesitated to use such
thing from the beginning, because it seemed to me like it would have
meant a nonlinear model rather than linear.. (Sorry, if the question
is stupid, I'm not that good at statistics)
Your earlier description of the plots made me think both "a" and "b"
were right-skewed. Such a situation (if my interpretation were
correct) would seriously undermine the statistical validity of an
analysis like lm(a ~ b) .
--
David Winsemius, MD
West Hartford, CT
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