Time series influenced by half-time, intake and treatment...
Have you read Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer)? The latter part about nonlinear modeling with mixed effects sounds like it could help you a lot. 1. Consistent with that, I might start by averaging over all 15 people, then making plots and from the plots decide how to model everything else. 2. Then I'd try to fit that model to each person one at a time, as suggested by Pinheiro and Bates. 3. With the output from step 2, you can then use function "nlme" in package "nlme". 4. I case this does not bring sufficient enlightenment and you would like more help from this listserve, I suggest you read the posting guide! "www.R-project.org/posting-guide.html". I believe that questions more consistent with that posting guide tend to get more useful replies quicker. hope this helps.
K??re Edvardsen wrote:
Hi! First of all: I'm a newbie to both statistics and R, so please be patient with me... I do however, like R because I've been programming (pascal, IDL, perl, C etc) and designing models since -92, but never related to statistics. Ok, here we go: I've got a set of 15 people, all of them observed over 10 weeks (10 analysed blood samples) with - let us kall it the A-value - influenced by: 1) a half time of the A-value of ~3 weeks 2) intake through diet (constant in time for each individ, but a big variation between the individs) 3) a treatment with a quick response, which may influence the A-value if "sufficient" dose is given. Problem: I do not know the limit for "sufficient" in 3). I also think there is a possibility the limit is individual, and thus may vary a lot between the individs. How do I approach such a problem? I know it's Friday, but I could not during the week figure out a model telling me if the treatment were significant or not... Anyone out there willing to guide me? Ked [[alternative HTML version deleted]]
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