Post-hoc test for interaction and time-series

I have a lmer model based on time-series data. The data is from an experiment with two treatments (“c” and “t”) and I have two individuals per treatment. I am trying to do a post-hoc test to determine if there is a difference in weight between the two treatments. I have tried using emmeans (see code below) but as far as I understand, the results from this is based on the difference between the treatments for a specific year (2000.5 in this case…). However, I’d like to find if there is a difference between the treatments, taking into account all of the years. Any advice would be greatly appreciated.


#make dataframe


#post-hoc test
compare <- emmeans(mod, specs = pairwise ~ year*treatment, type = "response")
plot<-plot(compare, comparisons = TRUE)

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