[R] linear mixed-effects models with two random variables?

[Bert Gunter]

Post on R-sig-mixed-models rather than here for better responses.

-- Bert

On Fri, Sep 14, 2012 at 2:19 AM, barbara costa <rbarbarahc at gmail.com> wrote:
> Dear R users,
> Does anyone knows how to run a glmm with one fixed factor and 2 random
> numeric variables (indices)? Is there any way to force in the model a
> separate interaction of those random variables with the fixed one?
> I hope you can help me.
>
> #eg.
> Reserve <- rep(c("In","Out"), 100)
> fReserve <- factor(Reserve)
> DivBoulders <- rep (c(1.23,2.4,1.26,1.78,1.97,1.35,1.23,2.4,1.26,1.78), 20)
> Roughness <- rep(c(3.45,2.56,1.32,5.67,3.73,3.57,2.66,1.52,7.67,2.73),20)
> Biomass <- rep(c(8,5.3,3.5,12,25.4,10.1,9.8,2.4,5.6,5.3),20)
>
> myData <- data.frame (fReserve ,DivBoulders ,Roughness ,Biomass )
>
> #glm
> glm1 <- glm (Biomass ~ fReserve * Roughness + fReserve *  DivBoulders  ,
> family= Gamma, data= myData)
>
> #glmm:
> library (nlme)
>
> lme1 <- lme (Biomass  ~  fReserve , random= ~1 + fReserve | Roughness +
> DivBoulders  , data=  myData ) # random intercept and slope
> #Error in getGroups.data.frame(dataMix, groups) :
>  # Invalid formula for groups
>  # if I only use one random variable I have:
> #Error in chol.default((value + t(value))/2) :
>   #the leading minor of order 2 is not positive definite
>
>
> lme2 <- lme( Biomass  ~  fReserve , random = ~1 | Roughness +
> DivBoulders  ,data=myData) #random
> intercept
> #Error in getGroups.data.frame(dataMix, groups) :
>  # Invalid formula for groups
> # if I only use one random variable my result is fine!
>
>
> lme3 <- lme (Biomass   ~  fReserve  , random=  ~ Roughness +   DivBoulders
> | fReserve   , data= myData ) # from help (lme)
> summary (lme3)
> # I have a result. Is the model correct for what I want?
> # BUT my fixed effect (reserve) does not have a p-value due to zero degrees
> of freedom. However in glm1 it has.
>
> Can you help me please?
>
> Thanks a lot in advance,
> Barbara
>
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>
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-- 

Bert Gunter
Genentech Nonclinical Biostatistics

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