Thanks for your feedback.
Actually Plant is nested since High and Low are qualitative relative
values (High in Michigan is not the same as High in Sienna).
S Ellison wrote:> The Plant classification is not nested; it's an effect across all
> countires and states and probably a fixed effct (assuming you want to
> measure its size or significance). But the state is nested in country.
>
> That would suggest to me
> lmer(Reaction~Drug+Plant+(1|Country/State),...)
>
> (or Plant*Drug, if you want an interaction)
>
> However, though your states are nested in countrythey are readily
> identifiable by lmer as different for each country (you do not have
> country1: State1, State2..., Country2:State1,State2..) so the nesting by
> country probably doesn't need to be specified. I think the above would,
> _in this case_ be almost identical to
>
> lmer(Reaction~Drug+Plant+(1|Country)+(1|State),...)
>
>
>
>
>
>
>>>> Ubuntu Diego <ubuntu.diego at gmail.com> 01/12/2009
16:22:09 >>>
>>>>
> I saw different specifications for Random Effects and I'm confused
> about
> the use of "/" and the use of "(0+...|)" .
> Let say we have a nested structure where some countries have some
> several plants in different states and we measure the reaction to a
> drug.
>
> The list of Countries = USA, France, Italy
> The States for USA = Michigan, Florida, California
> The States for France = Paris, Orleans
> The States for Italy = Venezia, Sienna, Florence, Rome, Napoli ,
> Sicilia
>
> Plants were classified as High and Low
>
> is this the way to specify a possible model ?
>
> lmer(Reaction ~ Drug + (1| Country / State / Plant) , data)
>
> or should I use something like this
> A) lmer(Reaction ~ Drug + (0| Country / State / Plant) , data)
> B) lmer(Reaction ~ Drug + (1| Country ) + (0+Country | State / Plant) ,
>
> data)
> C) lmer(Reaction ~ Drug + (1| Country ) + (0+Country | State / Plant) +
>
> (0+Country + State | Plant), data)
> D) lmer(Reaction ~ Drug + (1| Country ) + (0+Country | State ) +
> (0+Country + State | Plant), data)
>
> Thanks
>
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