Maximum likelihood inference on a mixed conditionally and marginally specified regression model for genetic epidemiologic studies with two-phase sampling

Journal of the Royal Statistical Society. Series B: Statistical Methodology

Volumn 69, Issue 2, 2007, Pages 123-142

  Chatterjee, Nilanjan ^a   Chen, Yi Hau ^b  

^a NATIONAL CANCER INSTITUTE   (United States)

^b ACADEMIA SINICA   (Taiwan)

Author keywords

Case control studies; Gene environment interaction; Missing data; Outcome dependent sampling; Semiparametric methods

Indexed keywords

EID: 33847378049     PISSN: 13697412     EISSN: 14679868     Source Type: Journal    
DOI: 10.1111/j.1467-9868.2007.00580.x     Document Type: Article

References (28)

1. Breslow, N. E. and Cain, K. C. (1988) Logistic regression for two-stage case control data. Biometrika, 75, 11-20.
2. Breslow, N. E. and Chatterjee, N. (1999) Design and analysis of two-phase studies with binary outcome applied to Wilms tumour prognosis. Appl. Statist., 48, 457-468.
3. Breslow, N. E. and Holubkov, R. (1997) Maximum likelihood estimation of logistic regression parameters under two-phase, outcome-dependent sampling. J. R. Statist. Soc. B, 59, 447-461.
4. Chatterjee, N. and Carroll, R. J. (2005) Semiparametric maximum likelihood estimation exploiting gene-environment independence in case-control studies. Biometrika, 92, 399-418.
5. Chatterjee, N., Chen, Y. H. and Breslow, N. E. (2003) A pseudoscore estimator for regression problems with two-phase sampling. J. Am. Statist. Ass., 98, 158-168.
6. Flanders, W. D. and Greenland, S. (1991) Analytic methods for 2-stage case-control studies and other stratified designs. Statist. Med., 10, 739-747.
7. Foutz, R. V. (1977) Unique consistent solution to likelihood equations. J. Am. Statist. Ass., 72, 147-148.
8. Gohagan, J. K., Prorok, P. C., Hayes, R. B., Kramer, B. S. and PLCO Screening Trial Project Team (2000) The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial of the National Cancer Institute: history, organization, and status. Contr. Clin. Trials, 21, suppl., 251S-272S.
9. Horvitz, D. G. and Thompson, D. J. (1952) A generalization of sampling without replacement from a finite universe. J. Am. Statist. Ass., 47, 663-685.
10. Lawless, J. F., Kalbfleisch, J. D. and Wild, C. J. (1999) Semiparametric methods for response-selective and missing data problems in regression. J. R. Statist. Soc. B, 61, 413-438.
11. Marcus, P. M., Vineis, P. and Rothman, N. (2000) NAT2 slow acetylation and bladder cancer risk: a meta-analysis of 22 case-control studies conducted in the general population. Pharmacogenetics, 10, 115-122.
12. Moslehi, R., Chatterjee, N., Church, T. R., Chen, J., Yeager, M., Weissfield, J., Hein, D. W. and Hayes, R. B. (2006) Cigarette smoking n-acetyltransferase genes and the risk of advanced colorectal adenoma. Pharmacogenomics, 7, 819-829.
13. Neuhaus, J., Scott, A. J. and Wild, C. J. (2002) The analysis of retrospective family studies. Biometrika, 89, 23-37.
14. Neuhaus, J., Scott, A. J. and Wild, C. J. (2006) Family-specific approaches to the analysis of case-control family data. Biometrics, 62, 486-494.
15. Neyman, J. (1938) Contribution to the theory of sampling from human populations. J. Am. Statist. Ass., 33, 101-116.
16. Pepe, M. S. and Fleming, T. R. (1991) A nonparametric method for dealing with mismeasured covariate data. J. Am. Statist. Ass., 86, 108-113.
17. Prentice, R. L. (1986) Binary regression using an extended beta-binomial distribution, with discussion of correlation induced by covariate measurement error. J. Am. Statist. Ass., 81, 321-327.
18. Prentice, R. L. and Pyke, R. (1979) Logistic disease incidence models and case-control studies. Biometrika, 66, 403-411.
19. Reilly, M. and Pepe, M. S. (1995) A mean score method for missing and auxiliary covariate data in regression models. Biometrika, 82, 299-314.
20. Robins, J. M., Rotnitzky, A. and Zhao, L. P. (1994) Estimation of regression coefficients when some regressors are not always observed. J. Am. Statist. Ass., 89, 846-866.
21. Satten, G. A. and Kupper, L. L. (1993) Inferences about exposure-disease association using probability of exposure information. J. Am. Statist. Ass., 88, 200-208.
22. Scott, A. J. and Wild, C. J. (1997) Fitting regression models to case-control data by maximum likelihood. Biometrika, 78, 705-717.
23. Spinka, C., Carroll, R. J. and Chatterjee, N. (2005) Analysis of case-control studies of genetic and environmental factors with missing genetic information and haplotype-phase ambiguity. Genet. Epidem., 29, 108-127.
24. Umbach, D. M. and Weinberg, C. M. (1997) Designing and analyzing case-control studies to exploit independence of genotype and exposure. Statist. Med., 16, 1731-1743.
25. Walker, A. M. (1982) Anamorphic analysis: sampling and estimation for covariate effects when both exposure and disease are known. Biometrics, 38, 1025-1032.
26. Weaver, M. A. and Zhou, H. B. (2005) An estimated likelihood method for continuous outcome regression models with outcome dependent sampling. J. Am. Statist. Ass., 100, 459-469.
27. White, J. E. (1982) A two-stage design for the study of the relationship between a rare exposure and a rare disease. Am. J. Epidem., 115, 119-128.
28. Whittemore, A. S. and Halpern, J. (1997) Multi-stage sampling in genetic epidemiology. Statist. Med., 16, 153-167.