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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