06-18-2013 12:32 PM
I am having an issue debating whether to include an interaction treatment in my random statement. I ran an animal trial 3 times (due to lack of space for housing more animals). So I had 3 repetitions of animals. There were 3 treatments within each repetition and 5 animals per treatment. So 15 total animals that we measure weight (and other things) weekly per repetition. What I didn't expect was that each repetition is significantly different from each other. So I included repetition as a random statement (along with repeated week/subject=animal). Since the rep is different and the treatments are affected by rep, should I also include repetition*treatment within the random statement? If I run rep*treatment within the model statement as a fixed effect, it is not significant.
Any insight would be much appreciated....I'm very unsure as to what to do. Thanks in advance to everyone for your time!!
06-18-2013 12:40 PM
I would almost certainly include it as a random effect, if for no other reason than to get the denominator degrees of freedom more nearly correct. Set up what Stroup refers to as a skeleton ANOVA table and check for degrees of freedom and sources of variability. With a repeated measures design and a small dataset, I would also apply ddfm=kenwardrogers.
See W.W. Stroup (2013) Generalized Linear Mixed Models. CRC Press