As are mine for 5 repititions (Stata 10, XP):
clear
input ln_rr_m dosage collecc se_glst person_y case study_id study_e
0 0 1 0 39637 281 3 2
-.0725707 1.330824 1 .09000712 40218 265 3 2
-.1278334 2.439844 1 .09273151 40621 241 3 2
-.2613648 4.103374 1 .09935509 40956 198 3 2
-.4462871 7.430433 1 .10182739 41222 156 3 2
0 0 1 0 145258 219 7 2
-.1625189 1.212121 1 .10710753 141933 162 7 2
-.1392621 2.203856 1 .11429413 139945 151 7 2
-.198451 3.636364 1 .11990109 146011 132 7 2
-.4462871 7.493112 1 .14876455 143153 77 7 2
0 0 1 0 34750 204 8 2
-.1508229 2.187076 1 .10585496 35154 164 8 2
-.0618754 3.827383 1 .10787362 35196 172 8 2
-.1625189 5.649946 1 .11324987 35488 156 8 2
-.328504 9.112817 1 .12940233 35529 148 8 2
0 0 1 0 23988 456 9 2
-.0943106 1.14482 1 .07583086 25050 381 9 2
-.1165338 2.289639 1 .08001615 24227 357 9 2
-.1863296 3.663423 1 .03711996 26115 386 9 2
end
forvalues i=1/5 {
glst ln_rr_m dosage if collecc==1, se(se_glst) cov(person_y case)
pfirst(study_id study_e) random
est sto glst`i'
}
Random-effects dose-response model Number of studies = 4
Iterative Generalized least-squares regression Number of obs = 15
Goodness-of-fit chi2(14) = 6.14 Model chi2(1) = 60.91
Prob > chi2 = 0.9628 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
ln_rr_m | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
dosage | -.0484551 .0062085 -7.80 0.000 -.0606236 -.0362866
------------------------------------------------------------------------------
Moment-based estimate of between-study variance of the slope: tau2 = 0.0e+00
/* OUTPUT OMITTED */
T
On Thu, May 7, 2009 at 4:31 PM, Martin Weiss <[email protected]> wrote:
>
> <>
>
> -glst- can be located via -findit glst-, you should add. How do the results
> differ? Mine are constant across ten repetitions...
>
>
> *************
> clear*
>
> input ln_rr_m dosage collecc se_glst person_y case study_id study_e
> 0 0 1 0 39637 281 3 2
> -.0725707 1.330824 1 .09000712 40218 265 3 2
> -.1278334 2.439844 1 .09273151 40621 241 3 2
> -.2613648 4.103374 1 .09935509 40956 198 3 2
> -.4462871 7.430433 1 .10182739 41222 156 3 2
>
> 0 0 1 0 145258 219 7 2
> -.1625189 1.212121 1 .10710753 141933 162 7 2
> -.1392621 2.203856 1 .11429413 139945 151 7 2
> -.198451 3.636364 1 .11990109 146011 132 7 2
> -.4462871 7.493112 1 .14876455 143153 77 7 2
>
> 0 0 1 0 34750 204 8 2
> -.1508229 2.187076 1 .10585496 35154 164 8 2
> -.0618754 3.827383 1 .10787362 35196 172 8 2
> -.1625189 5.649946 1 .11324987 35488 156 8 2
> -.328504 9.112817 1 .12940233 35529 148 8 2
>
> 0 0 1 0 23988 456 9 2
> -.0943106 1.14482 1 .07583086 25050 381 9 2
> -.1165338 2.289639 1 .08001615 24227 357 9 2
> -.1863296 3.663423 1 .03711996 26115 386 9 2
> end
>
> compress
> list, noobs // in 1/20 sepby(id)
>
> forv i=1/10{
> glst ln_rr_m dosage if collecc==1, se(se_glst) cov(person_y case)
> ///
> pfirst(study_id study_e) random
> }
> *************
>
> Output:
>
>
> Random-effects dose-response model Number of studies =
> 4
>
> Iterative Generalized least-squares regression Number of obs =
> 15
> Goodness-of-fit chi2(14) = 6.14 Model chi2(1) =
> 60.91
> Prob > chi2 = 0.9628 Prob > chi2 =
> 0.0000
> ----------------------------------------------------------------------------
> --
> ln_rr_m | Coef. Std. Err. z P>|z| [95% Conf.
> Interval]
> -------------+--------------------------------------------------------------
> --
> dosage | -.0484551 .0062085 -7.80 0.000 -.0606236
> -.0362866
> ----------------------------------------------------------------------------
> --
> Moment-based estimate of between-study variance of the slope: tau2 =
> 0.0e+00
>
>
> HTH
> Martin
>
> -----Ursprüngliche Nachricht-----
> Von: [email protected]
> [mailto:[email protected]] Im Auftrag von G Livesey
> Gesendet: Donnerstag, 7. Mai 2009 17:20
> An: [email protected]; [email protected]
> Betreff: st: Variable estimates from GLST metaregression of observational
> studies
>
> Dear Nicola and Statalisters,
>
> I am getting different estimates each time I run a glst command on the same
> dataset in Stata and would be glad of suggestions of how to resolve the
> problem.
>
> The glst command is used here to estimate the dose-dependency of effect in
> observational or relative risk data.
>
> The command and syntax, and extract from a dataset in use are shown below.
>
> I am using Stata v9.2, an up-to-date version of glst and the log data
> (ln_rr_m and corresponding errors se_glst) were obtained with gen double.
>
> I would very much appreciate help with this crucial problem.
>
> With thanks,
> Geoff. Livesey
>
>
> COMMAND AND SYNTAX:
> glst ln_rr_m dosage if collect_c==1, se(se_glst) cov(person_y case)
> pfirst(study_id studyexpression) random
>
>
> DATA:
> ln_rr_m dosage collec~c se_glst person_y case study_id study_e
> 0 0 1 0 39637 281 3 2
> -.0725707 1.330824 1 .09000712 40218 265 3 2
> -.1278334 2.439844 1 .09273151 40621 241 3 2
> -.2613648 4.103374 1 .09935509 40956 198 3 2
> -.4462871 7.430433 1 .10182739 41222 156 3 2
>
> 0 0 1 0 145258 219 7 2
> -.1625189 1.212121 1 .10710753 141933 162 7 2
> -.1392621 2.203856 1 .11429413 139945 151 7 2
> -.198451 3.636364 1 .11990109 146011 132 7 2
> -.4462871 7.493112 1 .14876455 143153 77 7 2
>
> 0 0 1 0 34750 204 8 2
> -.1508229 2.187076 1 .10585496 35154 164 8 2
> -.0618754 3.827383 1 .10787362 35196 172 8 2
> -.1625189 5.649946 1 .11324987 35488 156 8 2
> -.328504 9.112817 1 .12940233 35529 148 8 2
>
> 0 0 1 0 23988 456 9 2
> -.0943106 1.14482 1 .07583086 25050 381 9 2
> -.1165338 2.289639 1 .08001615 24227 357 9 2
> -.1863296 3.663423 1 .03711996 26115 386 9 2
>
>
>
>
>
>
>
>
> *
> * 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/
>
>
> *
> * 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/
>
--
To every ω-consistent recursive class κ of formulae there correspond
recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
belongs to Flg(κ) (where v is the free variable of r).
*
* For searches and help try:
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* http://www.stata.com/support/statalist/faq
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