st: RE: Spearman correlation with adjustment

[Nick Cox <n.j.cox@durham.ac.uk>]

My prejudice is that this isn't a very fruitful direction to be looking.  

Either you think in terms of modelling this properly, or you think in terms of different correlations. If they are very similar, no problem arises; if they are very different, it is hard to see that the idea of a single underlying correlation makes much sense. 

All that said, if the underlying issue is do methods agree, then arguably _concordance correlation_ is what you need: -findit concord-. 

A knock-down example is that corr(y, by) = 1 for _any_ positive b. In words, correlation measures linearity, not agreement. 

I wouldn't be that put off correlation by non-normality. You could always bootstrap it. 

Nick 
n.j.cox@durham.ac.uk 


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of cecilia sam
Sent: 06 October 2011 11:48
To: statalist@hsphsun2.harvard.edu
Subject: st: Spearman correlation with adjustment

Hi all,

I need to validate a method against another method. Since the data are
not normally distributed, I use spearman correlation using syntax
"spearman" to find correlation, and bland and altman plot to generate
the limit of agreement. I know that there are some confoundings, such
as weight and age. To adjust age, I have classified them into groups
and analysed the correlation for each group, while I want to present
an overall correlation. My question is:

Is there any syntax or method that I can use to adjust a single
continous (Not categorical) variable, or even adjust all of them at
once?

Many thanks.
Cheers from Cecilia
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