[R] cross-classified random factors in lme without blocking

[Peter Dalgaard]

Gordon Smyth <smyth at wehi.edu.au> writes:

> On page 165 of Mixed-Effects Models in S and S-Plus by Pinheiro and
> Bates there is an example of using lme() in the nlme package to fit a
> model with crossed random factors. The example assumes though that the
> data is grouped. Is it possible to use lme() to fit crossed random
> factors when the data is not grouped?
> 
> E.g., y <- rnorm(12); a=gl(4,1,12); b=gl(3,4,12). Can I fit an
> additive model like y~a+b but with a and b random?
> 
> Everything I've tried gives an error:
> 
>  > lme(y~1,random=~1|(a+b))
> Error in switch(mode(object), name = , numeric = , call = object,
> character = as.name(object),  :
>          [[ cannot be of mode (
>  > lme(y~1,random=~a+b)
> Error in getGroups.data.frame(dataMix, groups) :
>          Invalid formula for groups
> 

A standard trick is to define a grouping with one level:

one <- rep(1,length(y)
lme(...., random=~pdBlocked(.....)|one)

(Sorry, I'm a little rusty on the syntax, but just follow the example
in P&B)

AFAIR, it also works with random=list(a=~1,one=~b) and vice versa.

(The model is the same but you get different DF calculations, none of
which are correct in the completely balanced case...)

-- 
   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
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