Generalized linear random effects models with varying coefficients

Computational Statistics and Data Analysis

Volumn 43, Issue 1, 2003, Pages 13-28

  Tutz, Gerhard ^a   Kauermann, Göran ^b  

^a UNIVERSITY OF MUNICH   (Germany)

^b UNIVERSITY OF GLASGOW   (United Kingdom)

Author keywords

Generalized linear models; Local likelihood; Random effects models; Varying coefficients

Indexed keywords

LINEAR SYSTEMS; MATHEMATICAL MODELS; PARAMETER ESTIMATION;

LINEAR RANDOM EFFECTS;

DATA REDUCTION;

NUMERICAL MODEL;

EID: 0037880751     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9473(02)00205-0     Document Type: Article

References (25)

1. Abramowitz, M., Stegun, I. (Eds.), 1964. Handbook of Mathematical Functions. National Bureau of Standards, Washington, DC.
2. Aitkin M. A general maximum likelihood analysis of variance components in generalized linear models Biometrics 55 1999 218 234
3. Anderson D.A. Aitkin M. Variance component models with binary responses:interviewer variability J. Roy. Statist. Soc. Ser. B, Methodological 47 1985 203 210
4. Booth J. Hobert J. Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm J. Roy. Statist. Soc. Ser. B 62 1999 265 285
5. Breslow N.E. Clayton D.G. Approximate inference in generalized linear mixed model J. Amer. Statist. Assoc. 88 1993 9 25
6. Breslow N.E. Lin X. Bias correction in generalised linear mixed models with a single component of dispersion Biometrika 82 1995 81 91
7. Fahrmeir L. Lang S. Bayesian inference for generalized additive models based on Markov random fields Appl. Statist. 50 2001 201 220
8. Fan J. Gijbels I. Local Polynomial Modelling and its Applications 1996 Chapman - Hall London
9. Fan J. Heckman N.E. Wand M.P. Local polynomial kernel regression for generalized linear models and quasi-likelihood functions J. Amer. Statist. Assoc. 90 429 1995 141 150
10. Friedl H. Kauermann G. Standard errors for EM estimates in variance component models Biometrics 56 2000 761 767
11. Gourieroux, C., Montfort, A., 1989. Simulation based inference in models with heterogeneity. Technical Report 8902, Document de Travail INSEE/ENSAE.
12. Hartzel, J., Agresti, A., Caffo, B., 2001. Multinomial logit random effects models, preprint.
13. Hastie T. Tibshirani R. Generalized additive modelss:some applications J. Amer. Statist. Assoc. 82 398 1987 371 386
14. Hastie T. Tibshirani R. Varying-coefficient models J. Roy. Statist. Soc. Ser. B 55 1993 757 796
15. Hinde J. Compound poisson regression models Gilchrist R. GLIM 82 1982 109 121 Springer New York
16. Kauermann G. Tutz G. Local likelihood estimation in varying-coefficient models including additive bias correction J. Nonparametric Statist. 12 2000 343 371
17. Lin X. Zhang D. Inference in generalized additive mixed models by using smoothing splines J. Roy. Statist. Soc. Ser. B 61 1999 381 400
18. Loader C. Local Regression and Likelihood 1999 Springer Berlin
19. Longford N.T. Logistic regression with random coefficients Comput. Statist. Data Anal. 17 1994 1 15
20. McCulloch C.E. Maximum likelihood variance components estimation for binary data J. Amer. Statist. Assoc. 89 1994 330 335
21. McCulloch C.E. Maximum likelihood algorithms for generalized linear mixed models J. Amer. Statist. Assoc. 92 1997 162 170
22. Rao C. Linear Statistical Inference and its Applications 1973 Wiley New York
23. Rice J.A. Silverman B.W. Estimating the mean and covariance structure nonparametrically when the data are curves J. Roy. Statist. Soc. Ser. B 53 1991 233 243
24. Tutz, G., 2001. Generalized semiparametrically structured mixed models. Technical Report 251, Ludwig-Maximilians-Universität München, Institut für Statistik
25. Wolfinger R. O'Connell M. Generalized linear mixed models: A pseudo-likelihood approach J. Statist. Comput. Simulation 48 1993 233 243