Re: st: time in xtmixed

[William Buchanan <william@williambuchanan.net>]

How is your independent variable coded?  Did you use grand- or group-mean centering?  Have you tried fitting the model with polynomials for time?

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On Mar 25, 2013, at 6:12, megan rossi <megan_rossi@msn.com> wrote:

> 
> 
> How is this for confusing, when time is as a continuous variable (ie. option a)the association between depvar and indepvar is significant (time is borderline sig p=0.055), however as a categorical variable, option b, the relationship between depvar and indepvar becomes insignificant...and time 1 and 2 become very insignificant (p=0.55 and 0.17)
> In both scenario's the overall significance of the model is <0.0001 and log likelihoods are the same. The interaction between indepvar and time is only significant at time 0 not 1 or 2.
> If I did go with option a, could I really say that independent of time depvar and indepvar are association?
> Megan Rossi APD 
> PhD Candidate School of Medicine, University of Queensland
> Accredited Practicing Dietitian
> Princess Alexandra Hospital Nutrition & Dietetic Department
> m: 0402 931 441 | e: megan_rossi@msn.com 
> "Let food be thy medicine and medicine be thy food." — Hippocrates (ca. 460 – 377 BC)
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> 
>> Date: Mon, 25 Mar 2013 07:22:51 -0400
>> Subject: Re: st: time in xtmixed
>> From: dchoaglin@gmail.com
>> To: statalist@hsphsun2.harvard.edu
>> 
>> Megan,
>> 
>> To expand on Maarten's reply, i.time will give you separate effects
>> for the second and third time points (and the effect at the first time
>> point will be part of the constant term). If you use time as a
>> "continuous" predictor, its coefficient will be the slope of depvar
>> against time (adjusted for the contribution of indepvar), and the
>> constant term will correspond to time = 0. The second model is
>> simpler, but it assumes that the contribution of time is linear.
>> 
>> David Hoaglin
>> 
>> On Mon, Mar 25, 2013 at 3:06 AM, megan rossi <megan_rossi@msn.com> wrote:
>>> Hi Stata Guru's,
>>> Can anyone advise me on whether I need to include time variable as a categorical variable (ie. have a prefix i.) in xtmixed or can it be treated as a continous variable even though the data was collected at only three time points (evenly spaced). My research question: is depvar associated with indepvar independent of time ie. is syntax a or b most appropriate:
>>> a) xtmixed depvar indepvar time||ptid:time,cov(uns)
>>> or
>>> b) xtmixed depvar indepvar i.time||ptid:time,cov(uns)
>>> I noticed that the stata youtube video on this doesn't include i. however it was from 9 time points, not 3.
>>> Cheers,
>>> Megan Rossi APD
>> 
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