Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
From | "Tom Robinson" <tomrobnz@gmail.com> |
To | <statalist@hsphsun2.harvard.edu> |
Subject | st: marginsplot and transformed dependent variable |
Date | Thu, 25 Apr 2013 17:11:17 +1200 |
Hi, I am wanting to look at the effect of body mass index on CV risk factors (HbA1c, BP, lipids) in people with T2 diabetes. I am using linear regression to control for demographic variables and have categorized BMI. I would like to use margins and marginsplot to present the results. Mt problem is that the models that include the dependent variables (the CV risk factors) untransformed have poor post-estimation diagnostics i.e. non-normal residuals, heteroskedasticity, and poor fit If I transform the dependent variables (log or inverse) the models are much better. But then it is difficult to present the results to a general readership. Is it possible to take the transformed margins estimates and un-transform them? When I do it by hand they don't look right so maybe this doesn't make sense. Thanks for any advice Tom Tom Robinson 4 Domain St. Devonport ph. 445 2056 mob. 021 482 391 email. tomrobnz@gmail.com * * 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/