A pairwise likelihood approach to estimation in multilevel probit models

Computational Statistics and Data Analysis

Volumn 44, Issue 4, 2004, Pages 649-667

  Renard, Didier ^a   Molenberghs, Geert ^a   Geys, Helena ^a  

^a HASSELT UNIVERSITY   (Belgium)

Author keywords

Binary response data; Composite likelihood; Maximum marginal likelihood; Multilevel modeling; Pairwise likelihood; Penalized Quasi Likelihood

Indexed keywords

COMPUTATIONAL METHODS; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; DATA REDUCTION; ESTIMATION; MAXIMUM LIKELIHOOD ESTIMATION;

MULTILEVEL PROBIT MODELS; PAIRWISE LIKELIHOOD (PL) ESTIMATION;

STATISTICAL METHODS;

STATISTICAL ANALYSIS;

EID: 0344081997     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9473(02)00263-3     Document Type: Article

References (25)

1. Agresti A. Booth J.B. Hobert J.P. Caffo B. Random-effects modeling of categorical response data Sociol. Methodol. 30 1 2000 27-80
2. Anderson D.A. Aitkin M. Variance component models with binary response: interviewer variability J. Roy. Statist. Soc. Ser. B 47 2 1985 203-210
3. Arnold B.C. Strauss D. Pseudolikelihood estimation: some examples Sankhya Ser. B 53 2 1991 233-243
4. Besag J.E. Statistical analysis of non-lattice data Statistician 24 2 1975 179-195
5. Breslow N.E. Clayton D.G. Approximate inference in generalized linear mixed models J. Amer. Statist. Assoc. 88 1 1993 9-25
6. Breslow N.E. Lin X. Bias correction in generalized linear mixed models with a single component of dispersion Biometrika 82 1 1995 81-91
7. Cox D.R. Snell E.J. Analysis of Binary Data 2nd Edition 1989 Chapman - Hall London
8. Geys H. Molenberghs G. Ryan L. Pseudo-likelihood inference for clustered binary data Comm. Statist. Theory Methods 26 11 1997 2743-2767
9. Geys H. Molenberghs G. Lipsitz S.R. A note on the comparison of pseudo-likelihood and generalized estimating equations for marginal odds ratio models J. Statist. Comput. Simulation 62 1 1998 45-72
10. Goldstein H. Nonlinear multilevel models, with an application to discrete response data Biometrika 78 1 1991 45-51
11. Goldstein H. Multilevel Statistical Models 2nd Edition 1995 Edward Arnold London
12. Goldstein H. Rasbash J. Improved approximations for multilevel models with binary responses J. Roy. Statist. Soc. Ser. A 159 3 1996 505-513
13. Goldstein, H., Rasbash, J., Plewis, I., Draper, D., Browne, W., Yang, M. et al., 1998. A User's Guide to MLwiN. Institute of Education, London.
14. Heagerty P.J. Lele S.R. A composite likelihood approach to binary spatial data J. Amer. Statist. Assoc. 93 3 1998 1099-1111
15. Hedeker D. Gibbons R.D. A random-effects ordinal regression model for multilevel analysis Biometrics 50 4 1996 933-944
16. Kuk A.Y.C. Nott D.J. A pairwise likelihood approach to analyzing correlated binary data Statist. Probab. Lett. 47 4 2000 329-335
17. Le Cessie S. Van Houwelingen J.C. Logistic regression for correlated binary data Appl. Statist. 43 1 1994 95-108
18. Liang K.-Y. Zeger S.L. Longitudinal data analysis using generalized linear models Biometrika 73 1 1986 13-22
19. Lindsay B.G. Composite likelihood methods Contemp. Math. 80 1 1988 221-239
20. McCulloch C.E. Maximum likelihood variance components estimation for binary data J. Amer. Statist. Assoc. 89 2 1994 330-335
21. McCulloch C.E. Maximum likelihood algorithms for generalized linear mixed models J. Amer. Statist. Assoc. 92 1 1997 162-170
22. Renard D. Geys H. Molenberghs G. Burzykowski T. Buyse M. Validation of surrogate endpoints in multiple randomized clinical trials with discrete outcomes Biometrical J. 44 4 2002 1-15
23. Rodríguez G. Goldman N. An assessment of estimation procedures for multilevel models with binary responses J. Roy. Statist. Soc. Ser. A 158 1 1995 73-89
24. SAS Institute Inc., 1995. SAS/IML Software: Changes and Enhancements through Release 6.11. SAS Institute Inc., Cary, NC.
25. Zeger S.L. Karim M.R. Generalised linear models with random effects: a Gibbs sampling approach J. Amer. Statist. Assoc. 86 1 1991 79-102