[R-sig-ME] longitudinal analysis of nested samples

[Christopher Eckert]

Chris Eckert
Department of Biology
Queen's University
Kingston, Ontario K7L 3N6 Canada
chris.eckert at queensu.ca


> 
> Date: Mon, 17 Oct 2011 08:20:19 +0000
> From: "ONKELINX, Thierry" <Thierry.ONKELINX at inbo.be>
> To: Giancarlo Sadoti <gcsadoti at yahoo.com>,
> 	"r-sig-mixed-models at r-project.org"	<r-sig-mixed-models at r-project.org>
> Subject: Re: [R-sig-ME] longitudinal analysis of nested samples
> Message-ID:
> 	<AA818EAD2576BC488B4F623941DA74273B8A26EA at inbomail.inbo.be>
> Content-Type: text/plain; charset="iso-8859-1"
> 
> Dear Giancarlo,
> 
> You will need to have a look at your data. Since you claim that TR has 4 levels but the model output indicates only one (Number of obs: 560, groups: TR, 1).
> 
> The trees are nested within point. Therefore a more likely model is lmer(V ~ YR + (1|PT/TR), data=TREES) or lmer(V ~ YR + (1|PT) + (1|PT:TR), data=TREES) Both models are identical, the second is a bit more verbose but more clear. If the points are nested within transects then you can simply add it to the model: lmer(V ~ YR + (1|Transect) + (1|Transect:PT) + (1|Transect:PT:TR), data=TREES)
> 
> These are models with only a random intercept. You can add random slopes as well. E.g. if you want a random slope along year at the tree level:
> lmer(V ~ YR + (1|Transect) + (1|Transect:PT) + (1 + YR|Transect:PT:TR), data=TREES)
> 
> Best regards,
> 
> Thierry
> 
I am interested in this analysis and have a question for Dr. Onlelinx:
He suggested that for a random slopes and intercepts model, one would use:
> lmer(V ~ YR + (1|Transect) + (1|Transect:PT) + (1 + YR|Transect:PT:TR), data=TREES)
Why is the 4th term (1+ YR|Transect:PT:TR) why not just (YR|Transect:PT:TR)?
Thanks very much for any light you can shed on this.
I'm still coming to terms with lmer syntax.

Chris Eckert
Department of Biology
Queen's University
Kingston, ONtario, Canada