[Psn-general] Bootstrap and IGNORE statements

[Lindauer, A. (Germany) <And...@sg...>]

Dear PsN-Team and users,

I just came across an issue related to the bootstrap resampling when IGNORE statements are used in the code:

I have a big NONMEM dataset comprised of several studies and treatment arms. I exclude some arms/studies during modeling using IGNORE statements (e.g. placebo group).
Now, when I did a bootstrap, the resulting distributions looked kind of odd ('cauchy').  Then I realized what was going on: Although PsN applies the IGNORE statements correctly in each bootstrap replicate run, the resampling in the beginning is done on the entire dataset. So this means that there may be replicate datasets with a lot of e.g. placebo subjects that are going to be ignored during the run. Not only can this lead to odd distributions, but may also be the cause for crashing/unsuccessful replicate runs.
I know the issue can be partly addressed by using -stratify_on  - but this doesn't solve the problem completely.
As a workaround I'm running my bootstraps now on a subset of the original dataset, corresponding to the IGNORE statements used in the code.

Maybe in a future version of PsN the resampling could be done AFTER applying the IGNORE/ACCEPT statements to the dataset ? Or at least mentioning the issue in the documentation would be helpful.

Kind regards, Andreas.

Andreas Lindauer, PhD
Agriculture, Food and Life
Life Science Services - Exprimo
Senior Consultant
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