I have a data set of seed germination (germinated / failure) and I'm trying to understand whether germination rates of treatments differed from control. We made a randomised blocked experiment in which in each experimental unit (Plots) we had five seeds. We have two time points where germination data was measured (T1 and T2). Since we observed that several seeds germinated in the second time point, it is of our interest to include "time" as a variable and show this pattern. We are modeling the data through glmm in which we have successes and failures for each sampling unit:
cbind(successes,failures) ~ treatment * time + (1 | Blocks), family = binomial, link = logit
The question lies within the germination data. Should I keep what was computed in
T1 or only account what was recorded for
The successes of
T2 include the successes of
T2 will never have less successes than
T1 is within
T2). For example, Pot 1 had 2 out of 5 germinated seeds in T1 (40%), and in T2 it had 4 out of 5 (80%). But two of them were already in T1, so actually T2 had 2 germinated seeds out of 3 (66.6%).
Hope you'll understand the question.