I guess I'm missing some basic knowledge and I may be overlooking something important here...
Background: I have a dataset in which animals from 4 different groups (1 control and 3 treatment groups) underwent grip strength testing. Each trial consisted of ~5 measurements. In order to see how the treatment groups were different from the controls, a linear mixed model was done using the lmer function from lme4 as follows:
model1
Did you check the matrix produced by the result? Sometimes the difference is in the number of datapoint in the result output.
All of them are less than 0.02. However, you can select one of them based on your data and justify your selection.
I would be concerned about that ~5 measurements per trial. It would seem you want to do the same.number of measurements each time. The different number of measurements per trial would seem to make the experiment difficult to evaluate by the usual methods. If I'm not correct please let me know why. With best wishes, David Booth PS my thinking on this is that each experimental unit treatments should be the same for each unit.
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