[R] mixed effects model:how to include initial conditions

[christian_mora@vtr.net]

Christoph,

If you take a look at journal articles related to this topic published elsewhere,
you will find that the most common analysis is:

model<-lme(growth~initialsize+block+treatment+....)

maybe it would be important to check if your model really needs the interactions
you pointed out. I would suggest to try simpler models first....which generally
work OK in analysis of growth of plants, trees, etc

CM

>-- Mensaje Original --
>Date: Fri, 21 Jan 2005 12:30:07 +0100
>From: Christoph Scherber <Christoph.Scherber at uni-jena.de>
>To: r-help at stat.math.ethz.ch
>Subject: [R] mixed effects model:how to include  initial conditions 
>
>
>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.
>
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