Estimation in Generalized Linear Models with Heterogeneous Random Effects
نویسندگان
چکیده
The penalized quasi-likelihood (PQL) approach is the most common estimation procedure for the generalized linear mixed model (GLMM). However, it has been noticed that the PQL tends to underestimate variance components as well as regression coefficients in the previous literature. In this paper, we numerically show that the biases of the variance components are systematically related to the biases of the regression coefficient estimates, and also show that the biases of the variance components estimates of the PQL increase as random effects become more heterogeneous.
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