I'm using a linear mixed model with repeated measures to look at weight loss in groups of mice under various treatments. This has worked well, but in the present conditions we have groups of mice in which mortality is 100%; they survive for, say, 7 days and then have to be euthanized, while other treated groups have all or some members lasting through the end of the experiment (14 days).
I'm using SAS to calculate the probabilities. When at least one member of each group survives to 14 days, the program gives a between-group comparison, but when all members die, there is no group comparison. Obviously I don't expect comparisons for group-day effects after there are no members left, but it seems that there could be a comparison of the groups as a whole.
How can I approach this problem? Specifically, is there a way to use repeated measures when some but not all groups are completely removed partway through the study?
Edit to add an example figure:
In these figures, I would like to know whether Treatment 1 gives better survival than no treatment, whether Treatment 1 protects against disease (measured as weight loss) better than no treatment, whether Treatment 2 ditto, and also whether Treatment 1 gives better protection (both survival and weight loss) than Treatment 2.
Obviously, it's not possible to compare weight loss to "No treatment" after day 8. It should be possible before day 8, and it seems like it should be possible to compare Treatments 1 and 2 as groups, and/or after day 8. I've asked about repeated measures specifically, but the actual goal is to use whatever the most appropriate tool is to maximize information and thereby minimize animal use (i.e. animal distress); if there's a more suitable tag, let me know.