Re: st: Checking to see if the association between two variables is linear or otherwise

["Justina Fischer" <JAVFischer@gmx.de>]

Hi

unless education is measured in years I would create a set of dummy variables in educational level (i.education). 

The effect of low education on BMI will then be driven by the systematic relation with BMI that exists for the _majority_ of the low-edu-population.

Pls do not forget to control for income - low education might correlate with low income, and low income earners may not afford healthy food.

HTH

Justina


-------- Original-Nachricht --------
> Datum: Fri, 12 Oct 2012 21:56:35 +0000
> Von: Amal Khanolkar <Amal.Khanolkar@ki.se>
> An: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
> Betreff: st: Checking to see if the association between two variables is linear or otherwise

> Hi,
> 
> 
> I'm trying to figure out if linear regression is the appropriate choice
> for my research question - I would like to analyze the association of BMI and
> education (BMI is continuous and education categorical). Ideally I would
> just run a linear regression with BMI as the outcome and education as the
> principle explanatory variable. 
> 
> However my hypothesis is that low educated people are both likely to have
> a low and a high BMI, i.e. the association between education and BMI is
> probably more 'u shaped' than linear.
> 
> What is the best way to check if the association between a continuous and
> categorical variable is linear or otherwise...? Preferably, I would like to
> be able to plot such a shape using Stata.
> 
> Thanks,
> 
> /Amal.
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