Technical Papers

• Abramowitz, M. and Stegun, I.A. (1964). “Handbook of Mathematical Functions.” Nat. Bur. Stds. Applied Math. Stat. Series, no. 55.
  
• Agresti, A. (1990). “Categorical Data Analysis.” JohnWiley and Sons, Inc.
  
• Aitkin, M., Anderson, D., Francis, B. and Hinde, J. (1989). “Statistical Modelling in GLIM.” Oxford Sciences Publications. Oxford:Clarendon Press.
  
• Allison, P. D. (1995). “Survival Analysis Using the SAS System: A Practical Guide.” SAS Institute, Inc.
  
• Altham, P.M.E. (1971). “The Analysis of Matched Proportions.” Biometrika
  58(3):561–576.
  
• Altham, P.M.E. (1978). “Two Generalizations of the Binomial Distribution.” Appl. Statist. 27(2):162–167.
  
• Becher, H. (1991). “Alternative Parameterization of Polychotomous models: Theory and Application to Matched Case-Control Studies.” Statistics in Medicine, Vol 10, 375–382.
  
• Bradley, R.A. and Gart, J.J. (1962). “The Asymptotic Properties of ML Estimators when Sampling from Associated Populations.” Biometrika 49:205–214.
  
• Breslow, N.E. (1974). “Covariance Analysis of Censored Survival Data.” Biometrics 30:89–99.
  
• Breslow, N.E. and Day, N.E. (1980). Statistical Methods in Cancer Research, Vol. 1.
  The Analysis of Case-Control Studies. Oxford University Press.
  
• Breslow, N. (1984). “Extra-Poisson Variation in Log-Linear Models.” Appl. Statist. 33(1):38–44.
  
• Breslow, N.E. and Day, N.E. (1987). Statistical Methods in Cancer Research, Vol 2.
  The Design and Analysis of Cohort Studies. Oxford University Press.
  
• Breslow, N.E. and Storer, B.E. (1985). “General Relative Risk Functions for Case-control Studies.” American Journal of Epidemiology 122:149–162.
  
• Cernoff, H. (1954). “On the distribution of the likelihood ratio.” Ann. Math. Stat. 25:573–578.
  
• Cochran,W.G. (1943). “Analysis of Variance for Percentages Based on Unequal Numbers.” Journal of the American Statistical Association 38:287–301.
  
• Collett, D. (1991). Modelling Binary Data. Chapman and Hall.
  
• Collett, D. (1994). Modelling Survival Data in Medical Research. Chapman and Hall.
  
• Cox, D.R. and Oakes, D. (1984). Analysis of Survival Data. Chapman and Hall.
  
• Crowder, Martin J. (1978). “Beta-binomial Anova for Proportions.” Appl. Statist. 27(1):34–37.
  
• Dennis, J.E., and Schnabel, R.B. (1983). Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Prentice-Hall, Inc., New Jersey.
  
• Dyke, G.V. and Patterson, H.D. (1952). “Analysis of Factorial Arrangements when the Data are Proportions.” Biometrics 8:1–12.
  
• Efron, B. and Hinkley, D. V. (1978). “Assessing the Accuracy of the Maximum
  
• Likelihood Estimator: Observed Versus Expected Information.” Journal of the American Statistical Association 65:457–481.
  
• Fahrmeir, L. and Tutz, G. (1994). Multivariate Statistical Modelling Based on Generalized Linear Models. Springer-Verlag.
  
• Fienberg, S.E. (1977). The Analysis of Cross-classified Data. MIT press.
  
• Feigl, P. and Zelen, M. (1965). “Estimation of Exponential Survival Probabilities with Concomitant Information.” Biometrics 21:826–838.
  
• Frome, E.L. (1983). “The Analysis of Rates Using Poisson Regression Models.” Biometrics 39:665–674.
  
• Gail, M.H., Lubin, J.H., and Rubinstein, L.V. (1981). “Likelihood Calculations for Matched Case-control Studies and Survival Studies with Tied Death Times.” Biometrika 68:703–707.
  
• Gart, J.J. (1971). “The Comparison of Proportions: A Review of Significance Tests, Confidence Intervals and Adjustments for Stratification.” Rev. Int. Statis. Inst. 39:2.
  
• Griffiths, D.A. (1973). “Maximum Likelihood Estimation for the Beta-binomial Distribution and an Application to the Household Distribution of the Total Number of Cases of a Disease.” Biometrics 29:37–48.
  
• Hauck,W.W. and Donner, A. (1977). “Wald’s Test as Applied to Hypotheses in Logit Analysis.” Journal of the American Statistical Association 72(360):851–853.
  
• Haseman, J.K. and Hogan, M.D. (1975). “Selection of the Experimental Unit in Teratology Studies.” Teratology 12:165–172.
  
• Haseman, J.K. and Kupper, L.L. (1979). “Analysis of Dichotomous Response Data from Certain Toxicological Experiments.” Biometrics 35:281–293.
  
• Haseman, J.K. and Soares, E.R. (1976). “The Distribution of Fetal Death in Control Mice and its Implications on Statistical Tests for Dominant Lethal Effects.” Mutation Research 41:277–288.
  
• Hinde, J. (1982). “Compound Poisson Models.” In GLIM 82: Proceedings of the International Conference of Generalized Linear Models. Edited by R. Gilchrist.
  Springer-Verlag.
  
• Hosmer, D.W. and Lemeshow, S. (1989). Applied Logistic Regression. JohnWiley and Sons, Inc.
  
• Kalbfleisch, J.D. and Prentice, R.L. (1980). The Statistical Analysis of Failure Time Data. JohnWiley and Sons, Inc.
  
• Kennedy,W.J., and Gentle, J.E. (1980). Statistical Computing. Marcel Dekker, Inc..
  
• Kleinman, J. C. (1973). “Proportions with Extraneous Variance: Single and Independent Samples.” Journal of the American Statistical Association 68(341):46–54.
  
• Kupper, L.L. and Haseman, J.K. (1978). “The Use of a Correlated Binomial Model for the Analysis of Certain Toxicological Experiments.” Biometrics 34:69–76.
  
• Kupper, L.L., Portier, C., Hogan, M.D., andYamamoto, E. (1986). “The Impact of Litter Effects on Dose-Response Modeling in Teratology.” Biometrics 42:85–98.
  
• Lawless, J.F. (1982). Statistical Models and Methods for Lifetime Data. JohnWiley & Sons.
  
• Liang, K.-Y. and McCullagh, P. (1993). “Case Studies in Binary Dispersion.”
  Biometrics 49:623–630.
  
• L¨uning, K.G., Seridan,W., Ytterborn, K.H., and Gullberg, U. (1966). “The Relationship between the Number of Implantations and the Rate of Intra-uterine Death in Mice.” Mutation Res. 3:441–451.
  
• Lustbader, E.D., Moolgavkar, S.H., and Venzon, D.J. (1984). “Tests of the Null Hypothesis in Case-control Studies.” Biometrics 40:1017–1024.
  
• Mantel, N. (1967). “Some Statistical Viewpoints in the Study of Carcinogenesis.” In Progress in Experimental Tumor Research 11:431–443. S. Karger, Basel-NewYork.
  
• Mantel, N. (1987). “UnderstandingWald’s test for Exponential Families.” The
  American Statistician, 41(2):147–148.
  
• Mauritsen, R.H. (1984). “Logistic RegressionWith Random Effects.” Unpublished Ph.D. thesis, Department of Biostatistics, University ofWashington.
  
• McCullagh, P. and Nelder, J. A. (1989). “Generalized Linear Models.” Chapman and Hall.
  
• Mehta, C.R., Patel, N.R., and Gray, R. (1986). “Computing an Exact Confidence Interval for the Common Odds Ratio in Several 2×2 Contingency Tables.” Journal of the American Statistical Association 80:969–973.
  
• Moolgavkar, S.H. and Venzon, D.J. (1987). “Confidence Regions in Curved Exponential Families: Application to Matched Case-control and Survival Studies with General Relative Risk Functions.” Ann. Stat. 15(346):359.
  
• Morgan, B. J. T. (1992). “Analysis of Quantal Response Data.” Chapman and Hall.
  
• Nelder, J.A. and Mead, R. (1965). “A Simplex Method for Function Minimization.” Computer J. 7:308–313.
  
• Ochi,Y. (1983). “The Correlated Probit Regression of Binary Responses with Extra-binomial Variability.” Ph.D. thesis. Department of Biostatistics, University of Washington.
  
• Ochi,Y. and Prentice, R.L. (1983). “Regression Methods for Count Data with Extra-binomial Variation.” Pp. 127–139 in Atomic Bomb Survivor Data: Utilization and Analysis, edited by R. Prentice and D. Thompson. Philadelphia: SIAM.
  
• Paul, S.R. (1982). “Analysis of Proportions of Affected Foetuses in Teratological Experiments.” Biometrics 38:361–370.
  
• Pendergast, J., Gange, S. J., Newton, M. A., Linstrom, M. J., Palta, M., and Fisher, M. R. (1996). “A Survey of Methods for Analyzing Clustered Binary Response Data.” International Statistical Review 64:89–118.
  
• Pierce, D.A. (1976). “A Random Effects Model for Matched Pairs of Binomial Data.” Tech. report no. 55, Dept. of Statistics, Oregon State University.
  
• Pierce, D.A. and Sands, B.R. (1975). “Extra-Bernoulli Variation in Binary Data.” Tech. report no. 46, Dept. of Statistics, Oregon State University.
  
• Pregibon, D. (1981). “Logistic Regression Diagnostics.” Ann. of Stat. 9(4):705–724
  
• Prentice, R.L. (1986). “Correlated Binary Regression Using an Extended Beta-Binomial Distribution, with Discussion of Correlation Included by Covariate Measurement Error.” Journal of the American Statistical Association 81:321–327.
  
• Prentice, R.L. and Mason, M.W. (1986). “On the Application of Linear Relative Risk Regression Models.” Biometrics 42:109–120.
  
• Press,W.H., et al. (1992). Numerical Recipes in FORTRAN. Cambridge University Press.
  
• Segreti, A.C. and Munson, A.E. (1981). “Estimation of the Median Lethal Dose when Responses within a Litter are Correlated.” Biometrics 37:153–156.
  
• Self, S.G. and Liang, K. (1987). “Asymptotic Properties of Maximum Likelihood Estimator and Likelihood Ratio Tests under Nonstandard Conditions.” Journal of the American Statistical Association 82:605–610.
  
• Self, S.G. and Mauritsen, R.H. (1992). “Power Calculations for Likelihood Ratio Tests in Generalized Linear Models.” Biometrics 48:31–39.
  
• Shano, D.F. and Phua, K.H. (1976). “Algorithm 500, Minimization of Unconstrained Multivariate Functions [E4].” ACM Trans. on Math. Software 2(1):87–94.
  
• Shapiro, S., Sloan, D., et al. (1979) “Oral-Contraceptive Use in Relation to Myocardial Infarction.” Lancet, April 7, 1979, 743–746.
  
• Skellam, J.G. (1948). “A Probability Distribution Derived from the Binomial Distribution by Regarding the Probability of Success as Variable between the Sets of Trials.” J. Royal Statis. Soc. B 10(2):257–265.
  
• Southward, M.G. and Van Ryzin, J. (1972). “Estimating the Mean of a Random Binomial Parameter.” Proc. of the Sixth Berkeley Symposium on Math. Stat. and Prob. 4:249–263.
  
• Stiratelli, R., Laird, N. andWare, J. H. (1984). “Random Effects Models for Serial Observations with Dichotomous Response.” Biometrics 40:961–971.
  
• Storer, B.E. and Crowley, J. (1985). “A Diagnostic for Cox Regression and General Conditional Likelihoods.” Journal of the American Statistical Association 80:139–147.
  
• Storer, B.E.,Wacholder, S. and Breslow, N.E. (1983). “Maximum Likelihood Fitting of General Risk Models to Stratified Data.” Applied Statistics 32:172–181.
  
• Tarone, R.E. (1979). “Testing the Goodness of Fit of the Binomial Distribution.”
  Biometrika 66(3):585–590.
  
• Thomas, D.C. (1981). “General Relative Risk Functions for Survival Time and Matched Case-control Analysis.” Biometrics 37:673–686.
  
• Van Ryzin, J. (1975). “Estimating the Mean of a Random Binomial Parameter with Trial Size Random.” Sankhya 37(1):10–27.
  
• Væth, M. (1985). “On the Use ofWald’s Test in Exponential Families.” Int’l. Stat. Rev. 53(2):199–214.
  
• Wacholder, S. (1986). “Binomial Regression in GLIM: Estimating Risk Ratios and Risk Differences.” Am. J. Epi. 123(1):174–184.
  
• Weil, C.S. (1970). “Selection of the Valid Number of Sampling Units and a Consideration of their Combination in Toxicological Studies Involving Reproduction, Teratogenesis or Carcinogenesis.” Fd. Cosmet. Toxicol. 8:177–182.
  
• Wichmann, B.A. and Hill, I.D. (1982). “An efficient and portable pseudo-random number generator.” Applied Statistics 31, 188-190.
  
• Williams, D. (1975). “The Analysis of Binary Responses from Toxicological Experiments Involving Reproduction and Teratogenicity.” Biometrics 31:949–952.