SAS vs. SAS [RSABE / ABEL]
Hi Shuanghe,
don't worry. My results (using Johns code for ABE as given above at start of the thread) under SAS9.2 are:
Deleting the 4 subjects with missings (same happens in the intra-subject contrast calculations) gives
very similar to the numbers used for the RSABE criterion
.
But I don't believe in this numbers anyway. I think the optimizer stops here arbitrarily as almost ever for a partial replicate design in which the intra-individual variability for T is not identifiable.
Any modification to the code, f.i. fitting a model with no subject-by-treatment interaction via the CS covariance structure crashes with infinite likelihood and an estimate of s2wT=0!
I always wondered why the FDA insists on the Proc MIXED code, especially for that design.
On the other hand in the context of RSABE linearized criterion the point estimator and its 90% CI are calculated via intra-subject contrast T-R.
Why not use these results for ABE also
.
To increase the confusion here the results of the mighty oracle EMA code (same Proc GLM as for a 2x2 crossover for the PE and CI, s2wR from analysis of data for R (B) only):
So much numbers to choose between
.
❝ Now, my average BE gives:
❝ PE: 1.01021
, same as John's
❝ 90% CI: 80.7733 - 126.3450
, different from both of yours.
❝ Weird.
don't worry. My results (using Johns code for ABE as given above at start of the thread) under SAS9.2 are:
point est. 90% confidence interval
101.0213% 80.7733 126.3450
s2wR = 0.4210 -> CVwR = 72.35%
Deleting the 4 subjects with missings (same happens in the intra-subject contrast calculations) gives
point est. 90% confidence interval
90.5032% 73.5627 111.3449
s2wR = 0.4001 -> CVwR = 70.14%
very similar to the numbers used for the RSABE criterion

But I don't believe in this numbers anyway. I think the optimizer stops here arbitrarily as almost ever for a partial replicate design in which the intra-individual variability for T is not identifiable.
Any modification to the code, f.i. fitting a model with no subject-by-treatment interaction via the CS covariance structure crashes with infinite likelihood and an estimate of s2wT=0!
I always wondered why the FDA insists on the Proc MIXED code, especially for that design.
On the other hand in the context of RSABE linearized criterion the point estimator and its 90% CI are calculated via intra-subject contrast T-R.
Why not use these results for ABE also

To increase the confusion here the results of the mighty oracle EMA code (same Proc GLM as for a 2x2 crossover for the PE and CI, s2wR from analysis of data for R (B) only):
point est. 90% confidence interval
98.4476% 78.6492 123.2298
s2wR = 0.39824522 -> CVwR = 69.94%
So much numbers to choose between

—
Regards,
Detlew
Regards,
Detlew
Complete thread:
- FDA's HVD SAS Code from Progesterone Guidance jag009 2013-04-22 16:39
- Proc MIXED vs. Proc GLM Helmut 2013-04-22 17:47
- Proc MIXED vs. Proc GLM jag009 2013-04-22 20:33
- SAS vs. PHX Helmut 2013-04-22 22:10
- SAS vs. PHX Shuanghe 2013-04-23 11:45
- SAS vs. SASd_labes 2013-04-23 16:50
- SAS vs. SAS vs. Phoenix Helmut 2019-11-12 13:01
- SAS vs. SASd_labes 2013-04-23 16:50
- SAS vs. PHX jag009 2013-04-23 15:56
- SAS Warning (Note) on Proc Mixed jag009 2013-04-23 17:07
- Nut Job.. jag009 2013-04-30 21:09
- Second opinion (PHX 6.3) Helmut 2013-05-01 16:21
- Second opinion (PHX 6.3) jag009 2013-05-01 17:16
- Second opinion (PHX 6.3) ElMaestro 2013-05-01 18:48
- In praise of a full replicate Helmut 2013-05-01 19:16
- Third opinion d_labes 2013-05-02 12:00
- Compound Symmetry Helmut 2013-05-02 14:41
- Compound Symmetry - SASian (1) d_labes 2013-05-02 16:26
- Variance=0 Helmut 2013-05-03 16:07
- Compound Symmetry - SASian (1) d_labes 2013-05-02 16:26
- Compound Symmetry Helmut 2013-05-02 14:41
- Second opinion (PHX 6.3) jag009 2013-05-01 17:16
- Second opinion (PHX 6.3) Helmut 2013-05-01 16:21
- Nut Job.. jag009 2013-04-30 21:09
- SAS Warning (Note) on Proc Mixed jag009 2013-04-23 17:07
- SAS vs. PHX Shuanghe 2013-04-23 11:45
- SAS vs. PHX Helmut 2013-04-22 22:10
- Proc MIXED vs. Proc GLM jag009 2013-04-22 20:33
- Proc MIXED vs. Proc GLM Helmut 2013-04-22 17:47