[R-sig-ME] distribution of random effects glmmTMB - covariance structure
Vidal, Tiffany (FWE )
tiff@ny@vid@l @ending from @t@te@m@@u@
Thu Sep 6 19:59:05 CEST 2018
I'm unclear about the distributional assumptions regarding the random effects in glmmTMB, using different covariance structures. It is my understanding that the default is unstructured covariance structure. When estimating a vector of random effects, what is the assumption about the distribution of the factor levels within each grouping? I'm usually assuming normality with a mean of 0 and estimated variance. This doesn't seem to hold looking at the ranef(mod) for the different grouping variables.
mod <- glmmTMB(Count ~ us(time + 0|Subject))
mod <- glmmTMB(Count ~ diag(time + 0|Subject))
Here, I'm modeling (I think) variability among subjects through time (e.g., a different subject variance in each time step), and assuming that the repeated measures within each individual subject at time t, come from some distribution. If the assumed distribution was normal with a mean of 0, I would expect the sum of the Subject BLUPs in each year to approximate 0, but that doesn't appear to be the case. Any clarification on this would be appreciated.
[[alternative HTML version deleted]]
More information about the R-sig-mixed-models