Hi:

My question would be: what's the observational unit? If the individual is
the OU,
then I would go with (1). Since you randomly sampled populations within
type,
and presumably they are meant to be representative of a larger set of
populations,
I have no qualms about treating it as a random effect nested within a fixed
effect.
As it stands, it appears that you have a model with two nested sources of
variation:
that between and within populations.

HTH,
Dennis

On Tue, Apr 6, 2010 at 11:45 AM, Itay Mayrose <itaymay@gmail.com> wrote:

> Hi all,
>
>  This should be a somewhat trivial question but I am new to R and I am a
> bit
> puzzled with the lme syntax.
>
>  I would like to test for growth difference between three types of plants.
> For each plant type I randomly sampled four populations and for each
> population several individuals.
>
>  First, I used lme where type is the fixed effect and population is random
> nested within type, but I am not sure which of the three options the
> correct
> syntax is:
>
> (1)
>
> z1 <- lme(growth ~ type, random = ~ 1 | population, data =
> times,method="ML")
>
>  (2)
>
> z1 <- lme(growth ~ type, random = ~ 1 | type/population, data =
> times,method="ML")
>
>  (3)
>
> z1 <- lme(growth ~ type, random = ~ type | population, data =
> times,method="ML")
>
>
>
> I am using the ML method because I would like to contrast this model
> against
> a NULL model where growth does not depend on plant type (assuming the first
> syntax is correct):
>
> z0 <- lme(growth ~ 1, random = ~ type | population, data =
> times,method="ML")
>
> anova(z0,z1)
>
>
>
> Thanks!
> Khilik
>
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>
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