RE: st: gllamm or xtmixed models?

["Antonio Rodriguez Andres" <Antonio.Andres@emu.edu.tr>]

Alfonso

Can I specify the following model in xtmixed

xtmixed depression x1 x2 x3 || country : x2

Is incorrect to assume that the variable x2 (age let us say) vary across
countries (random slope) and at the same time is included as regressor?

Antonio

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Antonio Rodriguez
Andres
Sent: Friday, January 31, 2014 11:27 AM
To: statalist@hsphsun2.harvard.edu
Subject: RE: st: gllamm or xtmixed models?

Alfonso

Thank you for your answer. As far as I understood, as the observations are
clustered within countries. I have to account this in my model and use a two
multilevel model. What I can try is a fixed effects model with clustering at
country level

xtreg dv iv, fe vce (cluster country)

I should also use the xtset command but I do not have a real panel. Usually
we declare with xtset id year (both dimensions of the panel data ) but here
it is only a cross section

Can I type

xtset id  country  (1 level and second level)?


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Alfonso
Sánchez-Peñalver
Sent: Thursday, January 30, 2014 10:31 PM
To: Stata List
Subject: Re: st: gllamm or xtmixed models?

Hi again Antonio,

I haven't used -gllamm- (SSC) but my understanding is that you will also be
able to estimate the random effects with it. The fixed effects can be
estimated in two different ways:

1. Pooled OLS (-regress-) with a dummy variable for each country and no
constant (-nocons- option) 2. -xtreg- with fe option

For the second option you will have to first use -xtset- to identify which
is the level 2 (cluster) variable (country) and the level 1 variable (the
individuals).

As for random slopes, consider the random effects model. The random effects
model assumes that the intercept is a random variable across countries. What
if the intercept is not the only thing that varies across countries? What if
the effect (slope) of a certain variable (age let's say) also varies across
countries? You can include that variable in the random part of the command
to let the slope be a random variable as well. So for example, going back to
your syntax, assume that you believe the coefficient on x2 to be random as
well, you can type:

xtmixed depression x1 x3 || country: x2

Best,

Alfonso Sánchez-Peñalver, PhD

Visiting Assistant Professor
Suffolk University
Senior Instructor
UMass Boston



On Jan 30, 2014, at 3:09 PM, Antonio Rodriguez Andres
<Antonio.Andres@emu.edu.tr> wrote:

> Alfonso
> 
> Thank you for your answer.  On this way, can I estimate the fixed 
> effects for each country? What do they mean by random slopes for all data?
> This can be done using the xtmixed or gllamm command?
> 
> 
> 
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Alfonso 
> Sánchez-Peñalver
> Sent: Thursday, January 30, 2014 9:58 PM
> To: Stata List
> Subject: Re: st: gllamm or xtmixed models?
> 
> Hola Antonio,
> 
> I believe the correct syntax for the random effects model estimated 
> via maximum likelihood would be
> 
> xtmixed depression x1 x2 x3 || country:
> 
> Alfonso Sánchez-Peñalver, PhD
> 
> Visiting Assistant Professor
> Suffolk University
> Senior Instructor
> UMass Boston
> 
> 
> 
> On Jan 30, 2014, at 2:52 PM, Antonio Rodriguez Andres 
> <Antonio.Andres@emu.edu.tr> wrote:
> 
>> Dear stata users
>> 
>> I want to estimate multilevel models as I have observations for 
>> individuals across countries.  My dependent variable İs a measure of 
>> mental health ranging from 0 to 24. I want to use hierarchical linear 
>> models with fixed effects and random effects for countries. The 
>> correct syntax is:
>> 
>> xtmixed depression   x1 x2 x3   || i(country)
>> 
>> Any clue
>> 
>> Regards
>> 
>> Antonio
>> 
>> 
>> 
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