PROC GLM fixes Subject [🇷 for BE/BA]
Dear Kumar,
I would cite one of our Gurus:
You will also see that in FDA's code for 222BE which is based on PROC GLM there is a random statement pertaining to subject. One should think this means we are now asking PROC GLM to add a random effect (and thus to analyse as a mixed model), perhaps. It doesnt, though. PROC GLM with the random statement for subject still treats subject as a fixed effect. The bogus statement achieves another goal and compares sequence against the subject MS
Seems to be odd but here Subject is still fixed as ElMaestro wrote. So the experts are right (and ElMaestro too
)
I would cite one of our Gurus:
You will also see that in FDA's code for 222BE which is based on PROC GLM there is a random statement pertaining to subject. One should think this means we are now asking PROC GLM to add a random effect (and thus to analyse as a mixed model), perhaps. It doesnt, though. PROC GLM with the random statement for subject still treats subject as a fixed effect. The bogus statement achieves another goal and compares sequence against the subject MS
*--- GLM evaluation, output of T-R;
ODS output estimates=_est;
title "&file - GLM evaluation";
ods exclude ExpectedMeanSquares;
Proc GLM data=PKmetric;
class trt per seq subj;
model logvar=trt per seq subj(seq)/CLparm alpha=&al2;
random subj(seq)/test;
estimate 'T-R' trt -1 1;
run; quit;
*--- back-transformation;
title "&file - &Ominus2al.% confidence intervals, back-transformed";
data _est;
set _est;
pe=exp(estimate);
lower=exp(lowerCL);
upper=exp(upperCL);
run;
Seems to be odd but here Subject is still fixed as ElMaestro wrote. So the experts are right (and ElMaestro too

—
Kind regards,
Mittyri
Kind regards,
Mittyri
Complete thread:
- R code for analyzing classical 2X2 crossover designed bioequivalence data lizhao 2016-01-22 00:13 [🇷 for BE/BA]
- R code for analyzing classical 2X2 crossover designed bioequivalence data ElMaestro 2016-01-22 00:59
- R code for analyzing classical 2X2 crossover designed bioequivalence data lizhao 2016-01-22 01:26
- On random effects and bogus statements ElMaestro 2016-01-22 12:13
- FDA 'own' SAS code for 2x2 d_labes 2016-01-27 09:57
- FDA 'own' SAS code for 2x2 nobody 2016-01-27 10:09
- OT: PM to ElMaestro Helmut 2016-01-27 13:39
- On coffee and such... ElMaestro 2016-01-27 13:47
- FDA 'own' SAS code for 2x2 nobody 2016-01-27 10:09
- Geometric means ± SD Helmut 2016-01-27 13:51
- Geometric means ± SD nobody 2016-01-27 15:20
- Money makes the world go ’round Helmut 2016-01-27 16:11
- Money makes the world go ’round nobody 2016-01-27 16:31
- Fixed or random effect kumarnaidu 2016-11-04 14:05
- PROC GLM fixes Subjectmittyri 2016-11-04 23:00
- PROC GLM fixes Subject kumarnaidu 2016-11-05 05:22
- PROC GLM fixes Subject mittyri 2016-11-05 10:13
- PROC GLM fixes Subject kumarnaidu 2016-11-07 06:24
- PROC GLM fixes Subject mittyri 2016-11-07 11:57
- PROC GLM fixes Subject kumarnaidu 2016-11-07 12:42
- PROC GLM fixes Subject mittyri 2016-11-07 11:57
- PROC GLM fixes Subject kumarnaidu 2016-11-07 06:24
- PROC GLM fixes Subject mittyri 2016-11-05 10:13
- PROC GLM fixes Subject kumarnaidu 2016-11-05 05:22
- PROC GLM fixes Subjectmittyri 2016-11-04 23:00
- Fixed or random effect kumarnaidu 2016-11-04 14:05
- Money makes the world go ’round nobody 2016-01-27 16:31
- Money makes the world go ’round Helmut 2016-01-27 16:11
- Geometric means ± SD Ben 2016-11-08 21:20
- Misunderstanding Helmut 2016-11-09 15:29
- Misunderstanding Ben 2016-11-14 19:40
- RTFM Helmut 2016-11-14 21:50
- Misunderstanding Ben 2016-11-14 19:40
- Misunderstanding Helmut 2016-11-09 15:29
- Geometric means ± SD nobody 2016-01-27 15:20
- FDA 'own' SAS code for 2x2 d_labes 2016-01-27 09:57
- On random effects and bogus statements ElMaestro 2016-01-22 12:13
- R code for analyzing classical 2X2 crossover designed bioequivalence data lizhao 2016-01-22 01:26
- R code for analyzing classical 2X2 crossover designed bioequivalence data ElMaestro 2016-01-22 00:59