A Skew‐normal copula‐driven GLMM
In: Statistica Neerlandica: journal of the Netherlands Society for Statistics and Operations Research, Volume 70, Issue 4, p. 396-413
ISSN: 1467-9574
This paper presents a method for fitting a copula‐driven generalized linear mixed models. For added flexibility, the skew‐normal copula is adopted for fitting. The correlation matrix of the skew‐normal copula is used to capture the dependence structure within units, while the fixed and random effects coefficients are estimated through the mean of the copula. For estimation, a Monte Carlo expectation–maximization algorithm is developed. Simulations are shown alongside a real data example from the Framingham Heart Study.