So you made a baseline correction and now the team discusses ANCOVA [General Statistics]
❝ I read your post so many times now and I am somewhat confused.
And I read it over so many times exactly to avoid being too confusing. Sorry for failing.
❝ What were you actually trying to prove or disprove?
Uh, nothing, really, I only wanted to share my experience with this discussion in a BA-setting as I found it difficult to find anything that was just a simple statement or experience shared. And in favour of our position (Baselines are not(!) a good covariate in PK and will potentially result in a misleading result).
❝ Inclusion of a covariate one way or another makes an implicit assumption of a relationship that can be said to be linear between the covariate and the response (in the presence of the factors).
❝ If the variance goes full Tasmanian devil on you when you include the covariate then perhaps this assumption is...well... of a nature that has the potential to cause some degree of debate. And then that is where the problem truly is.
Nothing to add here. Back at university, I essentially learned that covariates
Remembering the qualities of the two teachers we enjoyed I will just say that statistics is not the most important issue for some university degrees.
❝ In contrast to classical anovas where an additional factor will always decrease the unexplianed variance (or leave it unchanged, academically), the inclusion of a covariate is not necessarily having this effect.
❝ Help me, please, I really wish to understand what this is all about.
Again, I am sorry. I thought it might be helpful for others who happen to come across the discussion whether or not to implement a baseline as a covariate in a PK evaluation to show in a simple made-up example how this has an impact and that it is not an appropriate idea.
- So you made a baseline correction and now the team discusses ANCOVA Relaxation 2018-02-13 15:37 [General Statistics]
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