DOE including events that occur or not occur on a certain time during the experimental runHow would you integrate events in a DOE? e.g. an event occurs on day 4 or day 5 or not at all . And if the event occurs there is a range to what extent this event occurs (30-100%). (let's assume you can control the event to occur or not to occur and to what extent, otherwise you would not add it to the design, but just record if it occurred and to what amount)
Simply adding factors will add the extent of the event to each experiment, even if the event does not occur. Unless you add disallowed combinations.
Is there a better, more efficient, or with more power way? e.g. using covariates?
Re: DOE including events that occur or not occur on a certain time during the experimental runMartin,
Are you talking about using a Uncontrolled factor, which is filled in after the run?
Can you use 0% for the case of no event?
Re: DOE including events that occur or not occur on a certain time during the experimental runIt is more like you start your experiment which last let's say 1 week, and you might add something to the process, like adding some oxigen to a culture. It could be on day 4 or day 5 or never. So it is kind of controlled when or if you add it, but it is not from the beginning. So staying with the oxigen example. The first 3 days the oxigen would be 0% and then on day 4 e.g. 40% (of potential 100% oxigen level) will be added. In another run there is no oxigen at all, and in another run on day 5 e.g. 60%, and so forth.
I understand you suggest to say if there will not be an event (adding oxigen) then use amount of 0%. To do this one would need for the day 3 levels (0,4,5) and a disallowed combination (if day == 4 or 5, then amount == 0 not allowed). And one saying (if day == 0, then amount !=0 not allowed)?
Re: DOE including events that occur or not occur on a certain time during the experimental runSounds complicated, @martindemel .
I've had questions like this from people in upstream biopharma, i.e. fermentation. They talk about different feeding regimes. I never had a good answer for them.
It could be handled as a functional input variable. But that might be over-complicating.
I think it depends how many different feeding regimes they want to explore. It might be easier just to code these as different levels of a single categorical factor. But that would depend on what questions they are trying to answer.
Sorry. I'm not sure if that helps much! I will be interested to know what they decide to do.
Phil
Re: DOE including events that occur or not occur on a certain time during the experimental runIt seems unnecessarily complicated. I do not think that a constraint is necessary. Just a data column for Oxygen level. As long as you know the amount present (0 if absent) for each run, it is just another potential factor. Regression can handle it. It might not be optimal data for estimating the intended model, but it should work.
I do not know of a principled method or tool to augment columns, only rows.
Re: DOE including events that occur or not occur on a certain time during the experimental runWhy not treat the feeding regime factor as categorical? For the analysis, you could still break out the %O2 by day, assuming data was collected daily.
Re: DOE including events that occur or not occur on a certain time during the experimental runThere is an approach to do this, described in one of Brad Jones' papers: https://www.tandfonline.com/doi/full/10.1080/00401706.2018.1562986
Don't have time right now to mock up and example, but if you want I can walk you through, I have used this approach previously.
