[1]
|
Breslow, N.E. and Clayton, D.G. (1993) Approximate Inference in Generalized Linear Mixed Models. Journal of the American Statistical Association, 88, 9-25.
|
[2]
|
Lin, X. and Breslow, N.E. (1996) Bias Correction in Generalized Linear Mixed Models with Multiple Components of Dispersion. Journal of the American Statistical Association, 91, 1007-1016.http://dx.doi.org/10.1080/01621459.1996.10476971
|
[3]
|
Lee, Y. and Nelder, J.A. (2001) Hierrarchical Generalized Linear Models: A Synthesis of Generalized Linear Models, Random Effect Models and Structured Dispersions. Biometrika, 88, 987-1006. http://dx.doi.org/10.1093/biomet/88.4.987
|
[4]
|
Karim, M.R. and Zeger, S.L. (1992) Generalized Linear Models with Random Effects; Salamnder Mating Revisited. Biometrics, 48, 681-694. http://dx.doi.org/10.2307/2532317
|
[5]
|
Booth, J.G. and Hobert, J.P. (1999) Maximizing Generalized Linear Mixed Model Likelihoods with an Automated Monte Carlo EM Algorithm. Journal of the Royal Statistical Society, 61, 265-285. http://dx.doi.org/10.1111/1467-9868.00176
|
[6]
|
Pan, J. and Thompson, R. (2003) Gauss-Hermite Quadrature Approximation for Estimation in Generalized Linear Mixed Models. Computational Statistics, 18, 57-78.
|
[7]
|
Pan, J. and Thompson, R. (2007) Quasi-Monte Carlo Estimation in Generalized Linear Mixed Models. Computational Statistics and Data Analysis, 51, 5765-5775. http://dx.doi.org/10.1016/j.csda.2006.10.003
|
[8]
|
Al-Eleid, E.M.O. (2007) Parameter Estimation in Generalized Linear Mixed Models Using Quasi-Monte Carlo Methods. PhD Dissertation, The University of Manchester, Manchester.
|
[9]
|
McCullouch, C.E. (2003) Generalized Linear Mixed Models. NSF-CBMS Regional Conference Series in Probability and Statistics Volume 7. Institution of Mathematical Statistics and the American Statistical Association, San Francisco.
|
[10]
|
McCulloch, P. and Nelder, J.A. (1989) Generalized Linear Models. 2nd Edition, Chapman and Hall, London. http://dx.doi.org/10.1007/978-1-4899-3242-6
|
[11]
|
Niederreiter, H. (1992) Random Number Generation and Quasi-Monte Carlo Methods. SIAM, Philadelphia. http://dx.doi.org/10.1137/1.9781611970081
|
[12]
|
Fang, K.T. and Wang, Y. (1994) Number-Theoretic Methods in Statistics. Chapman and Hall, London. http://dx.doi.org/10.1007/978-1-4899-3095-8
|
[13]
|
Pourahmadi, M. (1999) Joint Mean-Covariance Models with Applications to Longitudinal Data: Unconstrained Parameterization. Biometrika, 86, 677-690. http://dx.doi.org/10.1093/biomet/86.3.677
|
[14]
|
Pourahmadi, M. (2000) Maximum Likelihood Estimation of Generalized Linear Models for Multivariate Normal Covariance Matrix. Biometrika, 87, 425-435. http://dx.doi.org/10.1093/biomet/87.2.425
|
[15]
|
Shun, Z. (1997) Another Look at the Salamander Mating Data: A Modified Laplace Approximation Approach. Journal of the American Statistical Association, 92, 341-349. http://dx.doi.org/10.1080/01621459.1997.10473632
|
[16]
|
Ye, H. and Pan, J. (2006) Modelling Covariance Structures in Generalized Estimating Equations for Longitudinal Data. Biometrika, 93, 927-941. http://dx.doi.org/10.1093/biomet/93.4.927
|