I am trying to analyse some data from variety trials on forage grasses. The data consist of a range of multi-harvest pasture field experiments. Typically a single experiment would consist of 10-15 cultivars or candidate cultivars in randomized complete block design. After the year of establishment the experiment is typically harvested the 3 following years. One, most likely, naïve analysis using Proc Mixed, would be as follows: data t; infile ‘TESB.txt’; input field establ engar plot rep cult yield row col harvyr; run; proc mixed data=t method = reml; class rep cult harvyr; model yield = rep/ ddfm=kr; random cult harvyr; run; The variables to consider here are: rep – replication cult – cultivar yield – yield row – row number col – column number harvyr – harvest year However, I apparently do not account for the correlations in space and time here, and here is where I need help: First, how do I account for the spatial covariances among the field plots, e.g., the fact that neighbouring plots are more likely to be positively correlated? I realize that the ‘repeated’ statement is the one to use, but I cannot figure out how. BTW: each plot position is given my the row and col variables. Second, each plot is harvested in three subsequent years, so I would assume that this would cause positive correlations as well and should be included in the model. Ideally I would like to see both these covariances included simultaneously. Would really appreciate feedback here. Thank you.
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