Hi Elizabeth,

Sorry, my previous message was corrupted.

 
As I started to say, I think that you are missing a factor. I would
use 

m2 From: r-sig-mixed-models-bounces@r-project.org [mailto:r-sig-mixed-
 > models-bounces@r-project.org] On Behalf Of Elizabeth Graham
 > Sent: 21 October 2013 12:45
 > To: r-sig-mixed-models@r-project.org
 > Subject: [R-sig-ME] Error structure for split-split plot with
treatment
 > across blocks
 >
 > Hello,
 >
 > I am trying to create a LME model for a split-split-plot
experiment.
 >
 > My current model is as follows, based on the split-plot design
outlined
 > in Pinheiro and Bates 2000:
 >
 > model random=~1|Stream/Treatment/Shade/Leaves)
 >

 Question: Do you really want Treatment in the random-effects
structure?
 The main reason for asking is that in principle it is a two-level
fixed effect of interest, so it's a bit surprising to see it over on
the right at all. Further, from your data you have your streams nested
in Treatment which makes me wonder how it can be sensible to have a
random-effects spec that puts treatment nested in stream.

 Given that you probably want Treatment tested against the
Stream-level random effect that is essentially the replication level
per treatment, I'd have expected something like
 m2
summary(aov(log(density)~Treatment*Shade*Leaves+Error(Stream/Shade/Leaves),
data))

 testing Treatment against the random Stream effect and other effects,
but unsurprisingly returns a singular model (killing the
Stream/Treatment level of analysis) when adding Treatment in the Error
term.

 S Ellison

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