Hello, I was wondering if I could get some guidance/advice in using the glme function for a problem of mine: I have some continuous positive data C_ij representing accumulated quantities, where i denotes subject and j a state. The assumption here is that C_ij were accumulated at a constant rate within each state j, but these rates were different across states. We have the times t_ij where subjects spent in each state. We also have some other covariates, some time dependent, some not. The interest here is to model the mean rate conditional on state, as well as values of the other covariates. I was thinking of fitting a mixed model, with the following characteristics: - time values t_ij can be used as offset - the model will be of the Gamma family with log link, for convenience for the offset (log of times will be used) - the correlation between C_ij across j values within i will be expressed with one random effect expressing the random intercept per subject i - states will be categorical variable (choosing one of them as baseline) - what I am not sure about is if I also need to use time as weights. I want to model the fact that C_ij for longer times should have higher ?weight?, since the ?rate? is estimated over a longer period of accumulation. Any comment/suggestion would be greatly appreciated. Thanks, Nicholas
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