Re: [R] lm for log log

From: David Winsemius <dwinsemius_at_comcast.net>
Date: Sun, 20 Jun 2010 15:54:02 -0400

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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Received on Sun 20 Jun 2010 - 19:57:07 GMT

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