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.
