Statalist


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: st: Missing standard errors with xtmixed


From   Maarten buis <maartenbuis@yahoo.co.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Missing standard errors with xtmixed
Date   Fri, 17 Oct 2008 18:29:50 +0100 (BST)

A common trick is to translate xvar1 and xvar2 such that the value 0 is
meaningful, e.g. by substracting the mean or the minimum observed
value. Different translations can lead to very different estimated
variances and covariances of the random effects, and might lead to
convergence.

-- Maarten 

--- Glenn Goldsmith <glenn.goldsmith@gmail.com> wrote:

> I am trying to fit a linear mixed model using xtmixed with two random
> coefficients and a random intercept, using the following syntax: 
> 
> xtmixed depvar xvar1 xvar2 [otherxvars] if touse || groupid : xvar1
> xvar2,
> covariance(unstruct)
> 
> The model appears to converge, but two of the standard errors are
> missing,
> as shown below (all other standard errors are present):
>  
>
----------------------------------------------------------------------------
> --
>   Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf.
> Interval]
>
-----------------------------+----------------------------------------------
> --
> groupid: Unstructured        |
>                    sd(xvar1) |   .5210501   .0146728      .4930711
> .5506168
>                    sd(xvar2) |   .7152157   .0202753      .6765606
> .7560793
>                    sd(_cons) |   3.777054   .1089148      3.569505
> 3.996671
>            corr(xvar1,xvar2) |  -.8403815          .             .
> .
>            corr(xvar1,_cons) |   .2627643   .0004142      .2619524
> .2635758
>            corr(xvar2,_cons) |   -.739374          .             .
> .
>
-----------------------------+----------------------------------------------
> --
>                 sd(Residual) |   .8609064   .0026954      .8556397
> .8662056
>
----------------------------------------------------------------------------
> --
> LR test vs. linear regression:       chi2(6) =  6855.91   Prob > chi2
> =
> 0.0000
> 
> I'm not sure how to interpret this. Does it mean that the model has
> not
> actually converged? There are a number of "(not concave)" error
> messages in
> the iteration log, but no problems are reported in the final 5
> iterations.
> 
> Any suggestions for fixing the problem would be very gratefully
> received.
> I'm reluctant to impose a covariance structure, as there's little
> reason to
> think this is theoretically justified (indeed, part of my substantive
> interest is in the unstructured covariance estimates). 
> 
> Thanks in advance,
> 
> Glenn.
> 
> *
> *   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/
> 


-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands

visiting address:
Buitenveldertselaan 3 (Metropolitan), room N515

+31 20 5986715

http://home.fsw.vu.nl/m.buis/
-----------------------------------------

Send instant messages to your online friends http://uk.messenger.yahoo.com 
*
*   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/



© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index