Dear R users,
I am analyzing a dataset on growth of plants in response to several factors. I am using a mixed-effects model of the following structure:
model<-lme(growth~block*treatment*factor1*factor2, random=~1|plot/treatment/initialsize)
I have measured the initial size of the plants (in 2003) and thought it might be sensible to include this (random) variation into the random effects term of the model.
Is that correct? Or should "initialsize" rather be included as a covariate into the fixed effects term, as in:
alternative<-lme(growth~block*initialsize*treatment*factor1*factor2, random=~1|plot/treatment)
I would very much appreciate any suggestions on how to analyze these data correctly.
Best regards Chris.
I think you should include it as a covariate but not in the way you have written it. I would include it as a separate term, not in an interaction
alternative<-lme(growth~initialsize+block*treatment*factor1*factor2, random=~1|plot/treatment)
I recommend that you look carefully at the number of coefficients that you need to estimate in the model as you have specified it and perhaps change to an initial model that had more additive effects and fewer interactions.
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