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From |
Amal Khanolkar <Amal.Khanolkar@ki.se> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Checking to see if the association between two variables is linear or otherwise |

Date |
Fri, 12 Oct 2012 23:29:45 +0000 |

Hi Justina, Education is measured in years and the kind of degree qualification obtained - I have 6 categories of education: high school; no diploma, high graduate, some college, bachelors degree, masters degree etc I see that if I plot histograms for BMI separately for each educational group - the distribution of BMI gets narrower as educational level increases (as expected) - which made me wonder that assuming a linear relationship between education and BMI (and thus using linear regression) may not be the best choice. Do you mean, that I don't have to worry about the relationship being not linear then...? Thanks, /Amal, ________________________________________ From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Justina Fischer [JAVFischer@gmx.de] Sent: 13 October 2012 00:55 To: statalist@hsphsun2.harvard.edu Subject: Re: st: Checking to see if the association between two variables is linear or otherwise 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. > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: RE: st: Checking to see if the association between two variables is linear or otherwise***From:*"Justina Fischer" <JAVFischer@gmx.de>

**References**:**st: Checking to see if the association between two variables is linear or otherwise***From:*Amal Khanolkar <Amal.Khanolkar@ki.se>

**Re: st: Checking to see if the association between two variables is linear or otherwise***From:*"Justina Fischer" <JAVFischer@gmx.de>

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