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: [email protected]
http://myprofile.cos.com/mccaul
_______________________________________________
--- Mona Mowafi <[email protected]> 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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