Thank you Joseph. I was trying to reproduce the results in Garrett
Fitzmaurice book, Applied Longitudinal Analysis p.116-7 Tables 5.3-5.5
On Mon, Jan 5, 2009 at 4:30 AM, Joseph Coveney <[email protected]> wrote:
> Raphael Fraser wrote:
>
> I am trying to reproduce the code below in SAS into Stata. proc mixed
> by default uses restricted maximum likelihood. The model estimates the
> fixed effects and standard error.
> The options R and RCORR estimates the covariance and correlation
> matrices respectively.
> I can't seem to replicate the standard errors. Is there anyone that can
> help?
>
> PROC MIXED;
> CLASS id group time;
> MODEL y = group time group*time/ S CHISQ;
> REPEATED time/ TYPE = UN SUBJECT = id R RCORR;
>
> --------------------------------------------------------------------------------
>
> The PROC MIXED code calls for an unstructured patterned covariance matrix on
> the errors. Stata's -xtmixed- can't do that. -xtmixed- can apply an
> unstructured covariance matrix only to higher-level random effects.
>
> Someone showed a couple of years ago how you can get what you want, though.
> (I can't find the post in the Statalist archives at the moment, but I
> believe
> it was Yulia Marchenko who posted the method.) You basically insert a fake
> extra level so that all except the common variance of the residuals are now
> at
> the second level, where -xtmixed- can handle them as higher-level random
> effects.
>
> You can compare the results of the do-file below to the corresponding
> SAS PROC MIXED output shown in
> http://users.uoa.gr/~fsiannis/SAS/longitudinal/lab/tlc_profileanalysis.pdf
> to
> see that they're the same, including the standard errors of the
> fixed-effects
> estimates. (The SAS PROC MIXED code shown there happens to be identical to
> what you show above except for the name of the response variable.)
>
> Joseph Coveney
>
>
> clear *
> set more off
> infile id str1 group lead0 lead1 lead4 lead6 using ///
> http://users.uoa.gr/~fsiannis/data/longitudinal/tlcdata.txt
> quietly {
> reshape long lead, i(id) j(time)
> tabulate time, generate(time_)
> compress
> }
>
> * SAS drops the high values:
> char group[omit] "P"
> char time[omit] 6
>
> xi: xtmixed lead i.group*i.time || id: time_*, covariance(unstructured) ///
> noconstant nostderr variance nolrtest nolog
>
> * SAS displays the deviance, and not the log-likelihood:
> display in smcl as result %13.8f -2 * e(ll)
>
> * Covariances can be taken directly from the -xtmixed- output, but
> * variances need to be re-assembled:
> matrix define B = e(b)
> tempname temporary_matrix
> matrix define `temporary_matrix' = B[1,"lnsig_e:_cons"]
> scalar define s2_residual = exp(`temporary_matrix'[1,1])^2
> forvalues time_point = 1/4 {
> matrix define `temporary_matrix' = B[1,"lns1_1_`time_point':_cons"]
> scalar define s2_time`time_point' = exp(`temporary_matrix'[1,1])^2 + ///
> s2_residual
> display in smcl as result %7.4f s2_time`time_point'
> }
>
> exit
>
>
> *
> * 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/
>
--
Raphael A. Fraser, MSc
Lecturer in Biostatistics
Tropical Medicine Research Institute
Faculty of Medical Sciences
University of the West Indies
Mona Campus
Kingston, JAMAICA
Tel: (876) 927-2471; 977-6151
Mobile: (876) 410-4699
Fax: (876) 927-2984
e-mail: [email protected]
*
* 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/
