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# RE: st: Estout after xtmixed with ar(1) residuals

 From Dimitris Pavlopoulos To "statalist@hsphsun2.harvard.edu" Subject RE: st: Estout after xtmixed with ar(1) residuals Date Sun, 21 Mar 2010 13:20:01 +0100

```Dear Thoma,

thank you for your reply. I am doing what you suggest but it doesn't work.

Specifically, in estout, I am using the transformation "transform(ln*: exp(@) exp(@) r_ln*: exp(@) exp(@) at*: tanh(@) (1-tanh(@)^2) r_atr*: tanh(@) (1-tanh(@)^2))", so I am calculating  exp(r_lns2ose). Apparently it's not the correct transormation.

best regards,
Dimitris

________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Tom Trikalinos [ttrikalin@gmail.com]
Sent: Thursday, March 18, 2010 5:23 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Estout after xtmixed with ar(1) residuals

Just guessing here -- you should be able to work out quickly if I'm
right or wrong.

Typically in an ML routine you would optimize for t=log( of an SD or a variance)
this guarantees that the exp(t) (the SD or the variance) is non negative.

So I'm guessing that to get your variance or SE it should be exp(r_lns2ose)

Similarly for correlations. If they are allowed to range between -1
and 1, one probably optimizes for z=tanh^-1 of the correlation, as the
tanh(z) is bounded between -1 and 1.
However, in an autoregressive model the correlation should be between
0 and 1, no? So I would program the optimization so that the
back-transformation is 0.5*tanh(z)+0.5  -- bounded between 0 and 1.  I
dunno what Stata does.

Please, send an e-mail to the list when you've figured out.

Thomas A Trikalinos MD, PhD

Co-Director Tufts Evidence-based Practice Center
Associate Director, Center for Clinical Evidence Synthesis

Institute for Clinical Research and Health Policy Studies
Tufts Medical Center | 800 Washington St | Boston, 02111 MA

Phone: +1 617 636 0734
Fax:   +1 617 636 8628
email: ttrikalinos@tuftsmedicalcenter.org

On Thu, Mar 18, 2010 at 8:17 AM, Dimitris Pavlopoulos
<Dimitris.Pavlopoulos@soc.kuleuven.be> wrote:
> Dear all,
>
> I am trying to use estout after xtmixed (STATA 11 /SE). I am using a model with random slopes and an ar(1) stucture for the residuals. Stata 11 allows the estimation of separate correlation and residual standard deviation according to the values of a categorical variable. I have used this feature for a binary variable.
>
> My problem is that I cannot find which function is estout using to transform the standard deviation of the residuals that corresponds to value 1 of the grouping variable. So, for the residuals estout present:
>
> lnsig_e: variance for residuals corresponding to value 0 of grouping variable
> r_atr1: autoregressive correlation corresponding to value 0 of grouping variable
> r_lns2ose: variance for residuals corresponding to value 1  of grouping variable
> r_atr2: autoregressive correlation corresponding to value 1 of grouping variable
>
> for lnsig_e, I need to exponantiate to get the standard deviation
> For r_atr1 and r_atr2, I am using the tanh()  function.
>
> Does anybody know what function do I have to use to get the standard deviation from r_lns2ose?
>
> Thanks in advance?
>
> best regards,
> Dimitris
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```