On maximum hierarchical likelihood estimators

We show that in (large sample) cases where there is not sufficient information about the random effects, the maximum hierarchical likelihood estimators in a generalized linear mixed model (GLMM) may be inconsistent, even if the variance components are-known, This suggests that the behavior of such estimators in a GLMM may be quite different from that of the best linear unbiased estimators in linear mixed models.