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Re: st: Omnibus effects following xtmelogit with margins


From   "Michael N. Mitchell" <Michael.Norman.Mitchell@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Omnibus effects following xtmelogit with margins
Date   Fri, 24 Sep 2010 10:53:49 -0700

Dear Rob

Thanks for that additional information... so, there are really two different variables that represent a form of "time"... one being *day* (of which there are 10 levels), and one being *time* of day (of which there are 3 levels). If I have this right, then it seems to me that *time* is crossed with *day* (because every level of *time* appears with every level of *day*). So, the way that I am thinking about this as an HLM style model, I would write this as....

Level 1: Observations within subject
  Y = B0 + B1*Time1 + B2*Time2 + B3*Day + B4*cov1 + B5*cov2 + e

Level 2: Subject
  B0 = G00 + G01*group + u0
  B1 = G10 + G11*group + u1
  B2 = G20 + G21*group + u2

Then combining this into a composite model (for estimating in Stata), I would get....

  Y = G00 + G01*group +
      G10*Time1 + G11*Time1*group +
      G20*Time2 + G21*Time2*group +
      B3*Day + B4*cov1 + B5*cov2 + e + u0 + u1 + u2

  Then, in this fashion the model becomes...

. xtmelogit y i.group i.time#i.group i.day cov1 cov2 >0 ||subj: R.time, nolog

Note how I am formulating this as a two level model, with observations nested within subject, and that -time- and -day- are both at the same level, at level 1. They way that your model is formulated, it looks more to me like it is a three level model, with -time- and -day- each forming their own level. If this was something like time nested within students, and students nested within schools, I would think of this as a 3 level model, but I cannot (myself) help but think of your model as a 2 level model (which might be the lenses I am viewing this through). Maybe others have better lenses to share thoughts?

Best regards,

Michael N. Mitchell
Data Management Using Stata      - http://www.stata.com/bookstore/dmus.html
A Visual Guide to Stata Graphics - http://www.stata.com/bookstore/vgsg.html
Stata tidbit of the week         - http://www.MichaelNormanMitchell.com



On 2010-09-24 10.19 AM, Ploutz-Snyder, Robert (JSC-SK)[USRA] wrote:
Thanks Michael,

First... there was a glitch in my code-- the ">0 "was not supposed to be in the code (leftover from prev command that I stripped out).

The true command is:

xtmelogit y i.time##i.group cov1 cov2 ||subj: ||time:, nolog

Here is why... This is data from a completely nested experimental design, where y is measured 10 consecutive days at each of three times. The 10 replications are conducted because the thing we are measuring (viral load in a very small quantity sample) is very difficult to obtain, thus the 10 repetitions.  So we don't expect nor care to look for changes among the 10 consecutive measurements, but we do need to incorporate the cluster.


So per subject, y is obtained 10x per time, thus time is nested within subject.  I am not trying to model a random slope for time, but rather incorporate the double-nesting in my data.

Does that make more sense?






-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Michael N. Mitchell
Sent: Friday, September 24, 2010 12:05 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Omnibus effects following xtmelogit with margins

Dear Rob

    I wonder if you really want to specify the -xtmelogit- command as you have. I am
wondering if you really wanted to do what you showed (repeated below)...

. xtmelogit y i.time##i.group cov1 cov2>0 ||subj: ||time:, nolog

    or whether you want to do this...

. xtmelogit y i.time##i.group cov1 cov2>0 ||subj: time, nolog

    I am thinking you might have intended the latter because that specifies a random
intercept, as well as a random coefficient for the effect of time (at the subject level).
The question that remains for me is whether you need to do something special because
-time- is a factor variable, perhaps it is -||subj: R.time-, but I am not sure since I
have never done this and see very little documentation on this.

    If this is the way you want to specify your model, then I think it might solve your
-margins- problem.

I hope this helps,

Michael N. Mitchell
Data Management Using Stata      - http://www.stata.com/bookstore/dmus.html
A Visual Guide to Stata Graphics - http://www.stata.com/bookstore/vgsg.html
Stata tidbit of the week         - http://www.MichaelNormanMitchell.com



On 2010-09-24 8.26 AM, Ploutz-Snyder, Robert (JSC-SK)[USRA] wrote:
Happy Friday Statalisters.

I'm hoping someone can verify that -testparm- works appropriately to test the highest-order ominibus interaction effects following -xtmelogit- (as it works with xtmixed, for example). I also ran into a snag using -margins- as I usually do after an -xtmixed- model to obtain omnibus main effects for an ordinal factor variable.

   My model includes an indicator for time (three times) and an indicator for group (two groups) plus two continuous covariates.

xtmelogit y i.time##i.group cov1 cov2>0 ||subj: ||time:, nolog

...output omitted...


My test of the omnibus interaction effect  (as I would run following xtmixed) revealed:

. testparm time#group2

   ( 1)  [eq1]2.time#10000.group2 = 0
   ( 2)  [eq1]3.time#10000.group2 = 0

             chi2(  2) =    6.46
           Prob>   chi2 =    0.0396

But my use of -margins- to get the omnibus main effect for time (as I would with xtmixed) failed:

. margins time, asbalanced atmeans
default prediction is a function of possibly stochastic quantities other than e(b)
r(498);


Any assistance on this error?  Rob

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