Bioequivalence and Bioavailability Forum • once more about R and replicate designes

once more about R and replicate designes [🇷 for BE/BA]

posted by Astea – Russia, 2016-11-03 00:43 (3151 d 18:57 ago) – Posting: # 16767
Views: 21,278

Dear all!

While reading tonns of posts I stil can't understand how do SAS has got such a unique position? The method C for replicate studies (that is random effect with interactions PROC MIXED) in R (not only in bear but also in other packages) doesn't exist, does it?

As I understand only method A is available in bear and only for partial replicate designs 2x2x4, 2x2x6.. But what about fully replicated 2x4x4? VStus (in that post) mentioned that

❝ bear's lm.mod() was not confused by having more than 2 periods and 2 sequences

Also a question appears what should we use as a reference variance in order to apply scaling of confidence intervals (fully replicated design allows us even to estimate intrasubject variability of reference drug for two pairs of R that is we can desintegrate 2x4x4 for two 2x2x4 and estimate R variance independently for both. How will choosing one of them affect the scaling and possibility to fail?)

And the thing that is totally out of my mind: why should point estimation be affected by the way of analysis? As it was once shown by Helmut for balanced studies PE is just a means over periods and sequences. Why can't we do analogous in the case of inbalanced designs?

—
"Being in minority, even a minority of one, did not make you mad"

Complete thread:

Bear vs. Phoenix & SAS Helmut 2015-04-20 17:34
- R vs. Phoenix & SAS? yjlee168 2015-04-20 19:36
  - R vs. Phoenix & SAS? Helmut 2015-04-21 01:02
    - lme() does not work with all fixed effects yjlee168 2015-04-21 23:41
      - lme() does not work with all fixed effects Astea 2016-11-04 00:13
        
        lmer: Method B (PE catched for imbalanced dataset!!!) and Method C mittyri 2016-11-05 17:38
        
        lmer: Method B (PE catched for imbalanced dataset!!!) and Method C Astea 2016-11-05 19:27
        
        lmer: Method B is ready for scaling mittyri 2016-11-05 20:01
        
        lmer: Method B is ready for scaling Astea 2016-11-06 11:50
        
        lmer: Method B is ready for scaling mittyri 2016-11-07 06:07
- info for lsmeans yjlee168 2015-04-20 21:34
  - info for lsmeans Helmut 2015-04-21 01:15
    - once more about R and replicate designesAstea 2016-11-02 23:43
      - once more about R and replicate designes VStus 2016-11-06 11:34
        
        Getting variance components from the lmer output StatR 2017-02-03 13:53
        
        Getting variance components from the lmer output VStus 2017-02-03 15:47
        
        Getting variance components from the lmer output StatR 2017-02-03 17:12
        
        Getting variance components d_labes 2017-02-07 11:16
        
        Getting variance components StatR 2017-02-07 11:36
        Getting variance components StatR 2017-02-08 08:41
        
        Getting variance components d_labes 2017-02-08 10:13
        
        Getting variance components StatR 2017-02-08 10:19
        
        Data structure Helmut 2017-02-08 10:33
        
        Data structure StatR 2017-02-08 10:49