Abbie, I do not see anything regarding practical significance? How much weight gain is of scientific value? I don't see a column titled bodyweight, so I assume the column weight is bodyweight?
I'm really not sure what questions you are trying to answer or what hypotheses you are investigating. I'm not really sure how you are measuring weight? I seem to recall you are averaging weight per pen...If you are going to calculate an average, you should also consider the variation within pen. Not sure average is the appropriate statistic? How many animals are there per pen? What if you have one really large animal and the rest small, then the average is not an appropriate measure of central tendency.
Some of my thoughts:
1. It seems reasonable that animals will gain weight with age. What is the predicted amount of weight gain? Or perhaps, what is the historical amount of weight gain with age?
2. So is your question: Does the concentration or form of the feed affect weight gain (over and above "normal" weight gain)?
Plotting the data is a great way to start. I have attached a simple chart showing the weight by trial and age, coded by pen.
Weight vs. Age (days) separated by Trial
Obviously you have pen-to-pen variation (there may be a systematic pattern here).
Looking at that variation (within treatment so not influenced by concentration or form)
R of weight within treatment
So obvious age differences and pen-to-pen variation. Does not appear to be much due to the factors you manipulated, concentration and form. This could be due to the level setting of those factors (not sure why you chose 3 levels for concentration unless you predicted some non-linear effect) or they don't have an effect.
You can do fit model by age to remove this huge effect.
Funny how when these analyses start, there is always information not reported...Please keep in mind, that what analysis tools, what questions you can answer, what conclusions you can draw, your ability to extrapolate results, etc. ALL DEPEND ON HOW YOU GOT THE DATA!
The 32 sample of birds is a random sample of the birds within each pen. You are not actually tracking the same set of birds over time. Is your measurement system precise and stable? Did you ever measure the same bird at the same age more than once?
First I would determine if the variation you see in the response variables was of practical significance. Then I would do multivariate analysis of the multiple Y's. Do you expect any of the Y's to correlate (or not)? Why?
Weight is highly correlated with 1. Feed Intake, 2. FCR 3. Weight gain and 4. Uniformity though some of the patterns in the data are of interest.
Color/Mark by Column: Age exposes the relationships are significantly impacted by Age.
Doing the multivariate analysis BY AGE, may be more insightful. Example for Age = 7
Scatterplot Matrix
Notice above there is little relationship between Weight and Feed intake. And Weight and FCR are now negatively correlated.
I understand you tested concentration at 3 levels, but not why you did this? You have more information about concentration than you do about form. Not a bad thing, just need to realize the study is biased.
You do have some trial-to-trial differences (particularly regarding variation within treatment). You say the trials "everything was kept identical". This is, of course, is impossible. The key is understanding what changed between trials. I think you should treat trial as a block in the analysis. And since we don't know what changed between trials, assign it a random effect in the model. Since you likely have some knowledge that birds will increase in weight as they age, the questions are how do the factors (concentration and form) impact performance (Y's). If you had some historical data: weight over age, you might be able to look at the delta between "historical" and treatment effects. You might be able to look at the rate of weight gain (slope of the line). Also it looks like effects are different as the birds get older.
I would try fit model BY AGE.