Ken Peh
★    

Malaysia,
2014-05-05 20:44
(4426 d 03:52 ago)

Posting: # 12914
Views: 5,357
 

 Randomization before or after sample analysis [General Sta­tis­tics]

Dear Members,

We ran a BE study using William's design for 4 products, 1 original and 3 generic products. We used 28 subjects with 7 subjects in each treatment. One subject dropped out in one of the treatment phase. For William's design, we need to drop 3 more subjects to make it balance for statistical analysis. We randomize the subjects to be discarded. Should we randomize first the 3 subjects to be discarded before the analysis of plasma samples or we should randomize the subjects to be discarded after the analysis of plasma samples ? Which is the right approach ? :confused:

Appreciate your comments.

Thank you.

Regards,
Ken
d_labes
★★★

Berlin, Germany,
2014-05-06 10:09
(4425 d 14:27 ago)

@ Ken Peh
Posting: # 12916
Views: 4,312
 

 Dropping subjects to be balanced?

Dear Ken,

you really want discard 3 subjects with full data because an other one dropped out? :confused:
IMHO that's not a good idea. I guess that no regulatory body will accept such an approach, random choice of the subjects to be dropped or not.

Moreover there is no need to act this way. AFAIK the study is evaluable even if the balancedness of the original design is not maintained by drop-outs. SAS Proc GLM f.i. does the job without any problem.

It may be even worth considering to retain the data of the Drop-out to the extent they are available if the evaluation is done by the EMA recommended approach "use only the data relevant for the comparison under consideration". Or if you use mixed model analysis in the evaluation (not EMA!).

Regards,

Detlew
Tushar.g
☆    

India,
2014-05-06 15:41
(4425 d 08:55 ago)

@ Ken Peh
Posting: # 12918
Views: 4,224
 

 Randomization before or after sample analysis

Hi Ken,

Discarding subjects to make design balanced is not right, you would lose valuable information. It is Neither good idea nor any regulatory allow you to do so.
As Detlew said, SAS’s PROC GLM as well as WinNonlin will take care of calculation of unbalanced designs. Don’t worry.

❝ Which is the right approach ? :confused:


I would say, It will be cumbersome to justify the exclusion of subjects from regulatory point of view.


Regards,
Tushar
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