Combining binomial data using the logistic normal model

Journal of Statistical Computation and Simulation

Volumn 74, Issue 4, 2004, Pages 293-306

  Gao, Sujuan ^a  

^a INDIANA UNIVERSITY   (United States)

Author keywords

Homogeneity test; Penalized quasi likelihood; Variance components

Indexed keywords

EID: 1842853875     PISSN: 00949655     EISSN: None     Source Type: Journal    
DOI: 10.1080/0094965031000151169     Document Type: Article

References (24)

1. Abramowitz, M. and Stegun, I. (1972). Handbooks of Mathematical Functions. Dover, New York.
2. Anderson, D. A. and Aitkin, M. (1985). Variance components models with binary responses: Interviewer variability. Journal of Royal Statistical Society B, 47, 203-210.
3. Breslow, N. E. and Clayton, D. G. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Association, 88, 9-25.
4. Cox, D. R. (1970). The Analysis of Binary Data. Chapman and Hall, London.
5. Dean, C. (1992). Testing for overdispersion in Poisson and binomial regression models. Journal of American Statistical Association, 87, 451-457.
6. DerSimonian, R. and Laird, N. (1986). Meta-analysis in clinical trials'. Controlled Clinical Trials, 7, 177-188.
7. Harville, D. A. (1977). Maximum likelihood approaches to variance component estimation and to related problems. Journal of American Statistical Association, 72, 320-338.
8. Liang, K. Y. (1987). A locally most powerful test for homogeneity with many strata. Biometrika, 74, 259-264.
9. Lin, X. and Breslow, N. E. (1996). Analysis of correlated binomial data in logistic-normal models. Journal of Statistical Computation and Simulation, 55, 133-146.
10. Lin, X. (1997). Variance component testing in generalised linear models with random effects. Biometrika, 84, 309-326.
11. McCullagh, P. and Nelder, J. A. (1989). Generalized Linear Models. Chapman and Hall, London.
12. Prosser, R., Rasbash, J. and Goldstein, H. (1991). ML3 Software for Two-Level Analysis: Users Guide. Institute of Education, London.
13. Raghunathan, T. E. and Ii, Y. (1993). Analysis of binary data from a multicenter clinical trial. Biometrika, 80, 127-139.
14. SAS/OR Technical Report: The NLP Procedure, SAS Institute Inc., Cary, NC, USA, (1997).
15. Self, S. G. and Liang, K. Y. (1987). Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under nonstandard conditions. Journal of American Statistical Association, 82, 605-610.
16. Stiratelli, R., Laird, N. and Ware, J. H. (1984). Random effects models for serial observations with binary responses. Biometrics, 40, 961-971.
17. Stram, D. O. and Lee, J. W. (1994). Variance components testing in the longitudinal mixed effect models. Biometrics, 50, 1171-1177.
18. Stram, D. O. (1996). Meta-analysis of published data using a linear mixed-effects model. Biometrics, 52, 536-544.
19. Waclawiw, M. A. and Liang, K. Y. (1993). Prediction of random effects in the generalized linear model. Journal of the American Statistical Association, 88, 171-178.
20. Williams, D. A. (1982). Extra-binomial variation in logistic linear models. Applied Statistics, 31, 144-148.
21. Winship, D. (1978). Cimetidine in the treatment of duodenal ulcer. Gastroenterology, 74, 402-406.
22. Wolfinger, R. (1995). The GLIMMIX SAS Macro. SAS Institute Inc, Cary, NC.
23. Zeger, S. L., Liang, K.-Y. and Albert, P. S. (1988). Models for longitudinal data: A generalized estimating equation approach. Biometrics, 44, 1049-1060.
24. Zeger, S. L. and Karim, M. R. (1991). Generalized linear models with random effects: A Gibbs sampling approach. Journal of the American Statistical Association, 86, 79-86.