Using Historical Controls to Adjust for Covariates in Trend Tests for Binary Data

Journal of the American Statistical Association

Volumn 93, Issue 444, 1998, Pages 1282-1293

  Ibrahim, Joseph G ^a   Ryan, Louise M ^a   Chen, Ming Hui ^b  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^b WORCESTER POLYTECHNIC INSTITUTE   (United States)

Author keywords

Gibbs sampling; Historical data; Likelihood ratio test; Logistic regression; Posterior distribution; Prior distribution; Score test

Indexed keywords

EID: 0032276444     PISSN: 01621459     EISSN: 1537274X     Source Type: Journal    
DOI: 10.1080/01621459.1998.10473789     Document Type: Article

References (35)

1. Abelson, P. H. (1995), “Flaws in Risk Assessments,” Science, 270, 215.
2. Albert, J. H. (1988), “Computational Methods Using a Bayesian Hierarchical Generalized Linear Model,” Journal of the American Statistical Association, 83, 1037-1044.
3. Albert, J. H., and Chib, S. (1993), “Bayesian Analysis of Binary and Poly-chotomous Response Data,” Journal of the American Statistical Association, 88, 669-679.
4. Alden, C. J. (1994), “Toxicology and Carcinogenesis Studies of o-Benzyl-p-chlorophenol in F344/N Rats and B6C3F1 Mice,” NTP Technical Report 94-424, Washington, DC: U.S. Department of Health and Human Services.
5. Bailer, J. A., and Portier, C. J. (1988), “Effects of Treatment-Induced Mortality and Tumor-Induced Mortality on Tests for Carcinogenicity in Small Samples,” Biometrics, 44, 417-431.
6. Bedrick, E. J., Christensen, R., and Johnson, W. (1996), “A New Perspective on Priors for Generalized Linear Models,” Journal of the American Statistical Association, 91, 1450-1460.
7. Chen, C.-F. (1985), “On Asymptotic Normality of Limiting Density Functions With Bayesian Implications,” Journal of the Royal Statistical Society, Ser. B, 47, 540-546.
8. Chen, J. J., Kodell, R. L., Howe, R. B., and Gaylor, D. W. (1991), “Analysis of Trinomial Responses From Reproductive and Developmental Toxicity Experiments,” Biometrics, 47, 1049-1058.
9. Chen, M.-H. (1994), “Importance-Weighted Marginal Bayesian Posterior Density Estimation,” Journal of the American Statistical Association, 89, 818-824.
10. Chen, M.-H., and Shao, Q.-M. (1997), “On Monte Carlo Methods for Estimating Ratios of Normalizing Constants,” The Annals of Statistics, 25, 1563-1594.
11. Dellaportas, P., and Smith, A. F. M. (1993), “Bayesian Inference for Generalized Linear and Proportional Hazards Models via Gibbs Sampling,” Applied Statistics, 42, 443-459.
12. Dinse, G. E., and Lagakos, S. W. (1983), “Regression Analysis of Tumour Prevalence Data,” Applied Statistics, 32, 236-248.
13. Geisser, S. (1993), Predictive Inference: An Introduction, London: Chapman and Hall.
14. Gelfand, A. E., Sahu, S. K., and Carlin, B. P. (1996), “Efficient Parametri-sations for Generalized Linear Mixed-Models,” in Bayesian Statistics 5, eds. J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith, Oxford, U.K.: Oxford University Press, pp. 165-180.
15. Gelfand, A. E., and Smith, A. F. M. (1990), “Sampling Based Approaches to Calculating Marginal Densities,” Journal of the American Statistical Association, 85, 398-409.
16. George, I. E., and McCulloch, R. E., and Tsay, R. S. (1995), 'Two Approaches to Bayesian Model Selections With Applications,” in Bayesian Analysis in Econometrics and Statistics-Essays in Honor of Arnold Zellner, eds. D. A. Berry, K. A. Chaloner, and J. K. Geweke, New York: Wiley, pp. 339-348.
17. Gilks, W. R., and Wild, P. (1992), “Adaptive Rejection Sampling for Gibbs Sampling,” Applied Statistics, 41, 337-348.
18. Haseman, J. K., Huff, J., and Boorman, G. A. (1984), “Use of Historical Control Data in Carcinogenicity Studies in Rodents,” Toxocologic Pathology, 12, 126-135.
19. Ibrahim, J. G., and Laud, P. W. (1994), “A Predictive Approach to the Analysis of Designed Experiments,” Journal of the American Statistical Association, 89, 309-319.
20. Ibrahim, J. G., and Ryan, L. M. (1996), “Use of Historical Control Data in Time-Adjusted Trend Tests for Carcinogenicity,” Biometrics, 52, 1478-1485.
21. Kadane, J. (1980), “Predictive and Structural Methods for Eliciting Prior Distributions,” in Bayesian Analysis in Econometrics and Statistics-Essays in Honor of Harold Jeffreys, ed. A. Zellner, Amsterdam: North-Holland, pp. 89-93.
22. Laud, P. W., and Ibrahim, J. G. (1995), “Predictive Model Selection,” Journal of the Royal Statistical Society, Ser. B, 57, 247-262.
23. Laud, P. W., and Ibrahim, J. G. (1996), “Predictive Specification of Prior Model Probabilities in Variable Selection,” Biometrika, 83, 267-274.
24. Louis, T. (1982), “Finding the Observed Information Matrix When Using the EM Algorithm,” Journal of the Royal Statistical Society, Ser. B, 44, 226-233.
25. Meng, X. L., and Wong, W. H. (1996), “Simulating Ratios of Normalizing Constants via a Simple Identity: A Theoretical Exploration,” Statistica Sinica, 6, 831-860.
26. O'Neill, R. (1971), “Algorithm AS47-Function Minimization Using a Simplex Procedure,” Applied Statistics, 20, 338-345.
27. Oman, S. D. (1985), “Specifying a Prior Distribution in Structured Regression Problems,” Journal of the American Statistical Association, 80, 190-195.
28. Schervish, M. J. (1995), Theory of Statistics, New York: Springer-Verlag.
29. Seilkop, S. K. (1995), “The Effect of Body Weight on Tumor Incidence and Carcinogenicity Testing in B6C3F1 Mice and F344 Rats,” Fundamental and Applied Toxicology, 24, 247-259.
30. Tarone, R. (1982), “The Use of Historical Control Information in Testing for a Trend in Proportions,” Biometrics, 38, 215-220.
31. West, M. (1985), “Generalized Linear Models: Scale Parameters, Outlier Accommodations and Prior Distributions,” in Bayesian Statistics 2, eds. J. Bernardo, M. H. DeGroot, D. V. Lindley, and A. F. M. Smith, Amsterdam: North-Holland, pp. 531-557.
32. West, M., Harrison, P. J., and Migon, H. S. (1985), “Dynamic Generalized Linear Models and Bayesian Forecasting,” (with discussion), Journal of the American Statistical Association, 80, 73-97.
33. Winkler, R. L. (1980), “Prior Information, Predictive Distributions, and Bayesian Model-Building,” in Bayesian Analysis in Econometrics and Statistics-Essays in Honor of Harold Jeffreys, ed. A. Zellner, Amsterdam: North-Holland, pp. 95-109.
34. 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.
35. Zellner, A., and Rossi, P. E. (1984), “Bayesian Analysis of Dichotomous Quantal Response Models,” Journal of Econometrics, 25, 365-393.