We need to focus on your experimental design.   As specified in your model, Subject is random effects factor. The coding for Subject doesn't really matter--it's just an identification code specified as a classification factor in the CLASS statement. In your PROC MIXED output, Subject has values of   1 2 3 0.5 1.5 0.25 0.75 0.3333333333 0.6666666667   which suggests to me that you might not be thinking of Subject in an appropriate way (typically, Subject might be coded as a/b/c... or 1/2/3...). A model that is not consistent with the design would be the cause of zero df and missing p values, and too few observations for the model you have specified.   To help you sort this out, we need to know the details of your experimental design--something like a concise Methods section in a manuscript.   I hope this helps move you forward.     ... View more

You say that there was one pen per stocking rate. To clarify, does that mean that you had 4 pens in total, and 1 + 2 + 4 + 8 = 15 animals? ... View more

If you have a new question, I recommend starting a new thread. If you tap into an old thread, especially if it has already been answered, people may overlook your question.   Do you have intake data for each of the 3 feeds for each animal for each period, or do you have intake data for each of the 3 feeds for each pen for each period?   Was the amount of feed provided in the pen with 8 animals the same absolute quantity as the amount in the pen with 1 animal, or was it 8 times the amount? Did each pen eat appreciably less than the amount of each feed provided, or did the amount of feed provided impose some sort of constraint on consumption? For example, the pen ate all of its favorite feed and then moved to a less favored feed.   Are you pondering feed preference (in other words, preferential consumption of some feeds over others) as a consequence of stocking rate, as opposed to total consumption as a consequence of stocking rate? Do you plan to analyze consumption/preference of each feed separately? Or are you looking at compositional consumption (in other words, joint consumption of the three feeds, which might be thought of as diet allocation)?   How many pens did you have for each stocking rate?   In this study, pen is the experimental unit for stocking rate. It is not uncommon for people to think of animal as the experimental unit, but that is an incorrect assumption. Consequently, any measurements that you have on individual animals within a pen should be considered to be subsamples rather than true replicates. Plus, typically in studies like this, you have consumption by pen and not by individual animal within a pen.   Once we have a better understanding of your study, we can help you with your code. But you'll need to show what you've tried so far to give us something to work from.   And I have to ask, without intending to be mean but intending to point out the importance of planning ahead, Why did you not think about analysis before you collected your data? (You are definitely not alone in that approach, but it really is not in anyone's best interest.)   I hope this provides some clarity. Please follow up as need be.     ... View more

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