The concentration of a certain nutrient is measured in soil each fall after harvest in a set of research plots. I want to model the change in nutrient concentration over a number of years, but I'm inclined to express the time variable in days since the start of the study, as the number of days between measurements is not constant. Here's the SAS code of my present approach: PROC MIXED DATA = soil;
CLASS year plot;
MODEL concentration = daysIntoStudy / DDFM = kr;
REPEATED year / SUB = plot TYPE = ar(1) r;
RUN; I want to indicate an autoregressive covariance structure for the residuals as the same plots are being sampled each year, and I know that the repeated effect must be categorical, but I'm not sure if this is the right way to do it given that the variable year does not explicitly appear in the model. Is this correct? Also, should the predictor daysIntoStudy be specified as a random effect?
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