Modified estimating functions

Biometrika

Volumn 89, Issue 2, 2002, Pages 333-343

  Severini, Thomas A ^a  

^a NORTHWESTERN UNIVERSITY   (United States)

Author keywords

Asymptotic theory; Estimating equation; Likelihood inference; Nuisance parameter

Indexed keywords

EID: 3843150234     PISSN: 00063444     EISSN: None     Source Type: Journal    
DOI: 10.1093/biomet/89.2.333     Document Type: Article

References (26)

1. ADIMARI, G. & VENTURA, L. (2002). Quasi-profile loglikelihoods for unbiased estimating functions. Ann. Inst. Statist. Math. To appear.
2. BARNDORFF-NIELSEN, O. E. (1980). Conditionally resolutions. Biometrika 67, 293-310.
3. BARNDORFF-NIELSEN, O. E. (1983). On a formula for the distribution of the maximum likelihood estimator. Biometrika 70, 343-65.
4. BARNDORFF-NIELSEN, O. E. & Cox, D. R. (1994). Inference and Asymptotics. London: Chapman and Hall.
5. COX, D. R. (1993). Unbiased estimating functions derived from statistics that are functions of a parameter. Biometrika 80, 905-9.
6. FERGUSON, H., REID, N. & Cox, D. R. (1991). Estimating equations from modified profile likelihood. In Estimating Functions, Ed. V. P. Godambe, pp. 279-93. Oxford: Clarendon Press.
7. GIUMMOLÉ, F., VENTURA, L. & SALVAN, A. (2000). Estimating functions based on the modified directed likelihood. In Proceedings of the 15th International Workshop on Statistical Modelling, Ed. E. Ferreira and V. Nunez-Anton, pp. 433-6. Bilbao, Spain: Universidad del Pais Vasco.
8. GODAMBE, V. P. (1976). Conditional likelihood and optimum estimating equations. Biometrika 63, 277-84.
9. GODAMBE, V. P. (1991). Orthogonality of estimating functions and nuisance parameters. Biometrika 78, 143-51.
10. HALL, D. B. (2001). On the application of extended quasi-likelihood to the clustered data case. Can. J. Statist. 29, 77-97.
11. HALL, D. B. & SEVERINI, T. A. (1998). Extended generalized estimating equations for clustered data. J. Am. Statist. Assoc. 93, 1365-75.
12. HARVILLE, D. A. (1974). Bayesian inference for variance components using error contrasts. Biometrika 61, 383-5.
13. HARVILLE, D. A. (1977). Maximum likelihood approaches to variance component estimation and to related problems (with Discussion). J. Am. Statist. Assoc. 72, 320-40.
14. HUBER, P. J. (1981). Robust Statistics. New York: Wiley.
15. KALBFLEISCH, J. D. & SPROTT, D. A. (1970). Application of likelihood methods to models involving large numbers of parameters (with Discussion). J. R. Statist. Soc. B 32, 175-208.
16. KUMON, M. & AMARI, S. (1984). Estimation of a structural parameter in the presence of a large number of nuisance parameters. Biometrika 71, 445-59.
17. LIANG, K.-Y. (1987). Estimating functions and approximate conditional likelihood. Biometrika 74, 695-702.
18. LIANG, K.-Y. & ZEGER, S. L. (1995). Influence based on estimating functions in the presence of nuisance parameters (with Discussion). Statist. Sci. 10, 158-99.
19. LINDSAY, B. (1982). Conditional score functions: some optimality results. Biometrika 69, 503-12.
20. MCCULLAGH, P. & TIBSHIRANI, R. (1990). A simple method for the adjustment of profile likelihoods. J. R. Statist. Soc. B 52, 325-44.
21. MORTON, R. (1981). Efficiency of estimating functions and the use of pivots. Biometrika 68, 227-33.
22. PACE, L. & SALVAN, A. (1999). Point estimation based on confidence intervals: exponential families. J. Statist. Comp. Simul. 64, 1-21.
23. SEVERINI, T. A. (1998). An approximation to the modified profile likelihood function. Biometrika 85, 403-11.
24. SEVERINI, T. A. (1999). An empirical adjustment to the likelihood ratio statistic. Biometrika 86, 235-47.
25. SKOVGAARD, I. M. (1996). An explicit large-deviation approximation to one-parameter tests. Bernoulli 2, 145-65.
26. SPROTT, D. A. (1990). Inferential estimation, likelihood and linear pivotais (with Discussion). Can. J. Statist. 18, 1-15.