Hi all,
Still continuing on the dataset I have for the effect of two toxins on
rats, I managed to fit very nice linear mixed effects models for the
effects on the toxins on body weight over time, using weight = toxin * time
+ (time + 1 | subject.ID) as per Steven Pierce's suggestion.
I didn't need to get into a nonlinear mixed effect model as the results
were very nice staying within a linear framework.
The final analysis I need to do is to examine feed intake and see how this
is associated with body weight, time, and drug. I have feed intake measured
daily, so 28 intake data points per subject, but only 7 weight data points,
so while I have repeated measures for both, I do not have a fully linked
intake-weight series.
The research question is whether the toxin influenced feed intake (feed
palatability issue). I'm interested in intake slopes/partial slopes, but
obviously body weight should be the main driver of feed intake (heavier
rats eat more).
I'm thinking of an analysis similar to: intake = toxin*body weight*time
(time +1|subject.ID)
But I'm not sure I have the sample size to do a three-way effect, and I
don't know that this is the correct model specification given that I have
weight data which is not missing at random - all the rats were measured on
specific days such as Day 1, Day 4, Day 7.
Has anyone worked with a similar dataset to advise what model to fit.
Cheers
Michelle, note: I do not work Fridays
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