[R] Using lme() for split plot

[Bert Gunter]

Crossed Random effects are difficult using lme (wasn't designed for it). Try
lmer in the lme4 package if you need this. 


Bert Gunter
Genentech Nonclinical Biostatistics


-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
Behalf Of Joshua Stults
Sent: Thursday, May 07, 2009 3:02 PM
To: Rubén Roa-Ureta; r-help at r-project.org
Subject: Re: [R] Using lme() for split plot

That's a good example with a couple levels of nesting (similar to the
examples in the other book), but they still only have one factor,
'Variety', nested in each block.  Am I missing something?  Should I
make up a psuedofactor with four levels to code my two two-level
factors?


On Thu, May 7, 2009 at 5:46 PM, Rubén Roa-Ureta <rroa at udec.cl> wrote:
> Joshua Stults wrote:
>>
>> Hi,
>>
>> I'm trying to figure out how to use lme() for analyzing a split-plot
>> experiment.  I've been looking at the examples from the 'R Book',
>> those are nested but with only one factor at the whole-plot level, my
>> test is 2^2 at the whole-plot level, with a single many level factor
>> at the sub-plot level.  My question is about properly specifying the
>> random effects part of the model,
>>
>> lme( y ~ block + a*b*poly(c, n), random=~ ? )
>>
>> Where 'a' and 'b' are my two level whole-plot factors and 'c' is the
>> many level sub-plot factor.  I'm not sure what to use to get the right
>> error terms.  Do I use two error terms:
>>
>> random = ~ 1 | block/a + 1 | block/b
>>
>> or one:
>>
>> random = ~ 1 | block/a*b
>>
>> or something else entirely?  I haven't been able to find any relevant
>> examples on Google. Thanks for any suggestions/pointers.
>>
>>
>
> Have you checked Pinheiro and Bates 2004 Mixed-effects models in S and
> S-PLUS? They have a split-plot example starting on p. 45.
> Rubén
>



-- 
Joshua Stults
Website: http://j-stults.blogspot.com

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