Hello, I am working on analyzing some data using Proc Glimmix and my model was working well as evidenced by Gener. Chi-square/df ratio of less than 1 for a series of analysis when evaluating treatment, day, year, and interactions, however, when I am trying to be specific about treatment types my model is not working well. That brief overview aside here is what I am working with. I have a 4x2x2 factorial arrangement where there are 4 levels of grasses, 2 levels of brassicas, and 2 levels of legumes for a total of 16 treatments. We measured yield at 45, 70, and 90 days after planting in two years in a repeated measure fashion (or so I believe). There are 3 replications per treatment*day*year. I am looking to determine if grass types are different, brassica type is different, etc as well as differences in yield based on day and year and if there are interactions. I have been running treatment, day, year, and their interactions as fixed effects, with random effect of rep and rep within year and day. My model in SAS that is poor was this... class trt year day rep grass_type brass_type leg_type ; model grass = grass_type day year grass_type*day grass_type*year grass_type*day*year/ddfm=kenwardroger; random rep*day*year/subject=rep type=ar(1); Please help with this. Also, if you think that my fixed/random effects need to be different I would appreciate any additional help.
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