I agree that the design does not involve repeated measurements for the organ collection data, because each animal was assigned to only one level of HOUR.   However, there are repeated measurements on animals for the blood sample data. You have 5 measurements over time for 6 animals, 4 measurements over time for 12 animals, 3 measurements over time for 18 animals, and 2 measurements over time for 24 animals.   I think that, theoretically, if animals were randomly selected for sacrifice HOUR, you could proceed with modeling while assuming that the missing data were missing at random. But this is a relatively small study, and I would not make this assumption without considering the possibility of bias in the "random selection" for sacrifice.   I would plot the values of a given blood variable over all HOURs for each animal. Based on this plot, I would visually assess whether animals are tracking through time in a similar fashion, or whether some animals are following their own path through time. This plot would also inform you about the shape of the relationship through time; you might be able to use a more parsimonious model that the curvilinear model you are currently using, for example, an exponential decay model.   Given that the analysis of blood variables requires a mixed model, you'll want to switch to GLIMMIX or MIXED for analysis. You could also consider different ways to incorporate the pre-toxin measurements in your statistical model, particularly if the pre-toxin values varied appreciably among animals.    A regression on HOUR for each animal could be addressed with a random coefficients model (which essentially is a regression in a mixed model).   I hope this helps move your analysis forward.   ... View more