Resistant fits for regression with correlated outcomes an estimating equations approach

Journal of Statistical Planning and Inference

Volumn 75, Issue 2, 1999, Pages 415-431

  Qaqish, Bahjat F ^a   Preisser, John S ^b  

^a IL   (United States)

^b WAKE FOREST SCHOOL OF MEDICINE   (United States)

Author keywords

Cluster downweighting; Mallows class; Observation downweighting; Primary 62J12; Resistant; Schweppe class; Secondary 62F35

Indexed keywords

EID: 0042187915     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0378-3758(98)00158-x     Document Type: Article

References (18)

1. Carroll R.J., Pederson S. On robustness in the logistic regression model. J. R. Statist. Soc. B, 55:1993;693-706.
2. Godambe, Heyde, 1987. Quasi-likelihood and optimal estimation. Int. Statist. Rev. 55, 231-244.
3. Hampel, F.R., Ronchetti, E.M., Rousseeuw, P.J., Stahel, W.A., 1986. Robust Statistics: The Approach Based on Influence Functions. Wiley, New York.
4. Holland P.W., Welsch R.E. Robust regression using iteratively reweighted least-squares. Commun. Statist. Theor. Meth. A6(9):1977;813-827.
5. Huggins R.M. A robust approach to the analysis of repeated measures. Biometrics. 49:1993;715-720.
6. Kunsch H.R., Stefanski L.A., Carroll R.J. Conditionally unbiased bounded-influence estimation in general regression models, with applications to generalized linear models. J. Amer. Statist. Assoc. 84:1989;460-466.
7. Liang K.-Y., Zeger S.L. Longitudinal data analysis using generalized linear models. Biometrika. 73:1986;13-22.
8. Mancl, L., Leroux, B., 1996. Efficiency of regression estimates for clustered data. Biometrics 52, 500-511.
9. McCullagh, P., Nelder, J.A., 1989. Generalized Linear Models, 2nd ed. Chapman & Hall, London.
10. Morgenthaler S. Least-absolute-deviations fits for generalized linear models. Biometrika. 79:1992;747-754.
11. Morton Efficiency of estimating equations and the use of pivots. Biometrika. 68:1981;227-233.
12. Preisser J., Qaqish B. Deletion diagnostics for generalized estimating equations. Biometrika. 83:1996;551-562.
13. Preisser, J., Qaqish, B., 1999. Robust regression for clustered data with application to binary responses. Biometrics (in press).
14. Pregibon D. Resistant fits for some commonly used logistic models with medical applications. Biometrics. 38:1982;485-498.
15. Prentice R., Zhao Estimating equations for parameters in means and covariances of multivariate discrete and continuous responses. Biometrics. 47:1991;825-839.
16. Sen, P.K., Singer, J.M., 1985. Large Sample Methods in Statistics. Chapman & Hall, New York.
17. Singer J.M., Sen P.K. M-methods in multivariate linear models. J. Multivariate Anal. 17:1985;168-184.
18. Williams D.A. Generalized linear model diagnostics using the deviance and single case deletions. Appl. Statist. 36:1987;181-191.