I have a researcher who is conducting testing of area-wide treatments (done on large swaths of land, not easy to apply to small areas and not easy to replicate). There are two factors, factor A with three treatment levels (2 trt and 1 control) and factor B with two levels. The physical layout is like a split block (or strip plot), with each level of A applied to one of three vertical strips and each level of B applied to one of two horizontal strips (so each is like a whole plot factor), and the six subplots that are created by the criss-cross design will each have one level of the A*B interaction (so six combined treatment levels, each in one of six subplots). The outcome variable will be counts of insects, so likely Poisson unless the counts are large enough to be approximately normal. The counts will come from monitoring at 30 properties in each of the six subplots, so 180 observations total. I think the 30 properties are subsamples, not replicates, and the entire setup is established only once; there are no replicate blocks. If the design were repeated in multiple blocks, I think the appropriate code would be proc glimmix data = dat;
class block A B;
model response = A B A*B / dist= poisson link = log;
random block block*A block*B; But with no replicate blocks, I won't have block in the model, and I don't think I can estimate the A*B interaction without the replicates. I do, however, have the subsampling. I'm not sure how to proceed. The best I could think of was to add a random effect for the subplots to account for the subsampling and skip the interaction effect (which is essentially the same as the subplot though). proc glimmix data = dat;
class subplot A B;
model response = A B / dist= poisson link = log;
random subplot; Any suggestions? Edit: I attached a csv file, with subplot 1-6, factor A with 3 levels, factor B with 2 levels, properties 1-30 in each subplot, and simulated counts as response. DATA dat;
INFILE 'ExampleData.csv'
DSD MISSOVER PAD firstobs = 2;
INPUT subplot $ A $ B $ property $ response;
run;
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