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From | Maarten Buis <maartenlbuis@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: xtreg - continuous or discrete time |
Date | Wed, 17 Aug 2011 09:19:13 +0200 |
On Wed, Aug 17, 2011 at 2:49 AM, Ricardo Ovaldia wrote: > I have a longitudinal data on children measured at > ages 5, 10, 15 and 20. They were all measured > within two weeks of their birthday. > When using -xtreg-, I get very different results > depending of whether I use time as a continuous or > categorical variable. <snip> > What I do know is which is the most appropriate > parametrization of time. Or how to decide. The way to decide is to consider what it would mean when you enter time/age as a continuous variable. In that case you are stating that going from 5 to 10 years will have the same effect as going from 10 to 15 years, which will have the same effect as going from 15 to 20 years. Admittedly, these steps are the same in the sense that they are all 5 years apart, but if we think of a child growing up, than we would expect these steps to have wildly different implications for many aspects that we could be studying. Growing up is just not a linear process. I don't know what you are studying, and even if I did I am probably not an expert on that issue, so I cannot give you concrete advise on what is right. However, I can make your live even harder by giving you a third option: You can enter the main effect of time/age as a discrete variable and enter the interactions as continuous variables: growing up may be wildly non-linear, but differences between groups may change (approximately) linear over time. Technically, you could also enter the main effect of time as linear and the interactions as discrete, but in my experience the interaction terms tend to be rather sensitive to misspecification of the main effect. So I use as a rule of thumb that the main effect can be more flexible (e.g. categorical, or spline, or polynomial) than the interaction effect but not the other way around. But that is just my rule of thumb. Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/