My research investigates the carriage of Salmonella by raccoons captured on multiple occasions. I am interested in modelling the relationship between sampling interval (number of days between two captures) and the odds of a change in Salmonella serotype. My hypothesis is that a longer sampling interval is more likely to be associated with a change in serotype.
My question is related to how to generate this new variable. Is it valid to use all pairwise combinations of capture dates to generate sampling interval data? Although I was planning to account for clustering by raccoon using a random effect, I am concerned about the fact that I will be generating a LOT more data for certain raccoons which are captured 8 times (for example) as compared with raccoons which are only capture 2 times.
Is there any way to weight the new data I have generated by the number of captures? (to ensure that I have generated a proportional amount of new data using the existing data).
Could I use the weights option using
glm in R?