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Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS by Edward F. Vonesh

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Appendix

B

Additional results on estimation

In this appendix, we present some additional results as they pertain to the large sample behavior of different estimators under the GLME and GNLME models of Chapter 5. The emphasis is on comparing the asymptotic bias associated with the various estimators including those based on approximating the marginal moments using a first-order or second-order Taylor series expansion (i.e., PL/CGEE1, PL/QELS and CGEE2/PELS) and those based on approximating the marginal log-likelihood function using numerical integration such as Laplace-based MLE (LMLE) and MLE based on adaptive Gaussian quadrature (AGQ). We start first with a brief synopsis of each of the estimators.

B.1 The different estimators for mixed-effects ...

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