Dear R-Users:

I am trying to find the robust (or sandwich) estimates of the standard error of fixed effects parameter estimates using the package "lmer2". In model-1, I used "robust=TRUE" on the other, in model-2, I used "robust=FALSE". Both models giving me the same estimates. So my question is, does the robust option works in lmer2 to get the robust estimates of the standard error? If anybody could offer me a suggestion I would greatly appreciate it. Thank you.  

Model-1:

> p.mle<-lmer2(ddimer~race+steroid+psi+sofa+apache + (apache|subject), method="ML", data=final, robust=TRUE, cluster="id", weights=final$w)
> beta=fixef(p.mle)
> Vcov=vcov(p.mle, useScale=FALSE)
> se=sqrt(diag(Vcov))
> beta
 (Intercept)         race      steroid          psi         sofa       apache 
 5.826489820 -0.001920670 -0.242040171  0.005293996  0.075468340  0.009245152 
> se
[1] 0.108325229 0.058921371 0.055975547 0.001285687 0.018119089 0.002559902

Model-2:

> p.mle<-lmer2(ddimer~race+steroid+psi+sofa+apache + (apache|subject), method="ML", data=final, robust=FALSE, cluster="id", weights=final$w)
> beta=fixef(p.mle)
> Vcov=vcov(p.mle, useScale=FALSE)
> se=sqrt(diag(Vcov))
> beta
 (Intercept)         race      steroid          psi         sofa       apache 
 5.826489820 -0.001920670 -0.242040171  0.005293996  0.075468340  0.009245152 
> se
[1] 0.108325229 0.058921371 0.055975547 0.001285687 0.018119089 0.002559902


Best Regards, 

Sattar


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