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RE: st: tobit?


From   "Kieran McCaul" <kamccaul@meddent.uwa.edu.au>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: tobit?
Date   Wed, 13 Aug 2008 08:50:27 +0800

Since BMI is weight divided by height squared, why not regress weight on
SES while adjusting for height squared?

______________________________________________
Kieran McCaul MPH PhD
WA Centre for Health & Ageing (M573)
University of Western Australia
Level 6, Ainslie House
48 Murray St
Perth 6000
Phone: (08) 9224-2140
Phone: -61-8-9224-2140
email: kamccaul@meddent.uwa.edu.au
http://myprofile.cos.com/mccaul 
_______________________________________________

--- Mona Mowafi <mmowafi@hsph.harvard.edu> wrote:
> I have a dataset in which I am evaluating the effect of SES on BMI
> and BMI is heavily skewed toward obesity (i.e. over 50% of the sample
> >30 BMI).  I preferred to run a linear regression so as to use the
> full range of data, but the outcome distribution violates normality
> assumption and I've tried ln, log10, and sqrt transformations, none
> of which work.
> 
> Is it appropriate to use tobit for modeling BMI in this instance?  If
> not, any suggestions?


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