[R-sig-ME] specifying independence of random effects?

ONKELINX, Thierry Thierry.ONKELINX at inbo.be
Thu Dec 10 17:59:24 CET 2009

Dear Rob,

I suppose that IMPAIRMENT is a continunous variable. In that case you
can use (IMPAIRMENT - 1|DISCAT) + (1 |DISCAT) to indicate that the
random intercept and the random slope are independent. AFAIK you can
only specify a full variance-covariance matrix between random effects or
independent random effects. So structures like pdIdent, pdCompSymm, ...
are not available in lme4.



ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek
team Biometrie & Kwaliteitszorg
Gaverstraat 4
9500 Geraardsbergen

Research Institute for Nature and Forest
team Biometrics & Quality Assurance
Gaverstraat 4
9500 Geraardsbergen

tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be

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than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

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-----Oorspronkelijk bericht-----
Van: r-sig-mixed-models-bounces at r-project.org
[mailto:r-sig-mixed-models-bounces at r-project.org] Namens Rob Forsyth
Verzonden: donderdag 10 december 2009 17:31
Aan: r-sig-mixed-models at r-project.org
Onderwerp: [R-sig-ME] specifying independence of random effects?


I'm trying to specify a mixed-effect model describing "unmet NEED" (of
families with disabled children) as a function of IMPAIRMENT (i.e.  
intrinsic severity of the child's condition) and AREA of residence
(factor with ~15 levels). The impairment measure is a unidimensional
variable but it needs "calibrating" for separate types of disability
(autism, cerebral palsy etc) represented by another factor, DISCAT

In lmer syntax I have


but I want to specify independence of random effects. I'm aware of the
pdDiag options in the nlme library but unsure how to specify the model
in lme syntax?

Thank you


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