Agresti, A. (2002), Categorical Data Analysis, Second Edition, New York: John Wiley & Sons.
Aitkin, M., Anderson, D., Francis, B., and Hinde, J. (1989), Statistical Modelling in GLIM, Oxford: Oxford Science Publications.
Akaike, H. (1979), “A Bayesian Extension of the Minimum AIC Procedure of Autoregressive Model Fitting,” Biometrika, 66, 237–242.
Akaike, H. (1981), “Likelihood of a Model and Information Criteria,” Journal of Econometrics, 16, 3–14.
Boos, D. (1992), “On Generalized Score Tests,” The American Statistician, 46, 327–333.
Cameron, A. C. and Trivedi, P. K. (1998), Regression Analysis of Count Data, Cambridge: Cambridge University Press.
Carey, V., Zeger, S. L., and Diggle, P. (1993), “Modelling Multivariate Binary Data with Alternating Logistic Regressions,” Biometrika, 80, 517–526.
Collett, D. (2003), Modelling Binary Data, Second Edition, London: Chapman & Hall.
Cook, R. D. and Weisberg, S. (1982), Residuals and Influence in Regression, New York: Chapman & Hall.
Cox, D. R. and Snell, E. J. (1989), The Analysis of Binary Data, Second Edition, London: Chapman & Hall.
Davison, A. C. and Snell, E. J. (1991), “Residuals and Diagnostics,” in D. V. Hinkley, N. Reid, and E. J. Snell, eds., Statistical Theory and Modelling, London: Chapman & Hall.
Diggle, P. J., Liang, K.-Y., and Zeger, S. L. (1994), Analysis of Longitudinal Data, Oxford: Clarendon Press.
Dobson, A. (1990), An Introduction to Generalized Linear Models, London: Chapman & Hall.
Firth, D. (1991), “Generalized Linear Models,” in D. V. Hinkley, N. Reid, and E. J. Snell, eds., Statistical Theory and Modelling, London: Chapman & Hall.
Fischl, M. A., Richman, D. D., and Hansen, N. (1990), “The Safety and Efficacy of Zidovudine (AZT) in the Treatment of Subjects with Mildly Symptomatic Human Immunodeficiency Virus Type I (HIV) Infection,” Annals of Internal Medicine, 112, 727–737.
Gamerman, D. (1997), “Sampling from the Posterior Distribution in Generalized Linear Models,” Statistics and Computing, 7, 57–68.
Gilks, W. (2003), “Adaptive Metropolis Rejection Sampling (ARMS),” software from MRC Biostatistics Unit, Cambridge, UK, http://www.maths.leeds.ac.uk/~wally.gilks/adaptive.rejection/web_page/Welcome.html.
Gilks, W. R., Best, N. G., and Tan, K. K. C. (1995), “Adaptive Rejection Metropolis Sampling with Gibbs Sampling,” Applied Statistics, 44, 455–472.
Gilks, W. R., Richardson, S., and Spiegelhalter, D. J. (1996), Markov Chain Monte Carlo in Practice, London: Chapman & Hall.
Gilks, W. R. and Wild, P. (1992), “Adaptive Rejection Sampling for Gibbs Sampling,” Applied Statistics, 41, 337–348.
Hardin, J. W. and Hilbe, J. M. (2003), Generalized Estimating Equations, Boca Raton, FL: Chapman & Hall/CRC.
Hilbe, J. (1994), “Log Negative Binomial Regression Using the GENMOD Procedure,” in Proceedings of the Nineteenth Annual SAS Users Group International Conference, Cary, NC: SAS Institute Inc.
Hilbe, J. M. (2007), Negative Binomial Regression, New York: Cambridge University Press.
Hilbe, J. M. (2009), Logistic Regression Models, London: Chapman & Hall/CRC.
Hirji, K. F., Mehta, C. R., and Patel, N. R. (1987), “Computing Distributions for Exact Logistic Regression,” Journal of the American Statistical Association, 82, 1110–1117.
Ibrahim, J. G., Chen, M.-H., and Lipsitz, S. R. (1999), “Monte Carlo EM for Missing Covariates in Parametric Regression Models,” Biometrics, 55, 591–596.
Ibrahim, J. G., Chen, M. H., and Sinha, D. (2001), Bayesian Survival Analysis, New York: Springer-Verlag.
Ibrahim, J. G. and Laud, P. W. (1991), “On Bayesian Analysis of Generalized Linear Models Using Jeffreys’ Prior,” Journal of the American Statistical Association, 86, 981–986.
Lambert, D. (1992), “Zero-Inflated Poisson Regression Models with an Application to Defects in Manufacturing,” Technometrics, 34, 1–14.
Lawless, J. F. (1987), “Negative Binomial and Mixed Poisson Regression,” The Canadian Journal of Statistics, 15, 209–225.
Lawless, J. F. (2003), Statistical Model and Methods for Lifetime Data, Second Edition, New York: John Wiley & Sons.
Liang, K.-Y. and Zeger, S. L. (1986), “Longitudinal Data Analysis Using Generalized Linear Models,” Biometrika, 73, 13–22.
Lin, D. Y., Wei, L. J., and Ying, Z. (2002), “Model-Checking Techniques Based on Cumulative Residuals,” Biometrics, 58, 1–12.
Lipsitz, S. H., Fitzmaurice, G. M., Orav, E. J., and Laird, N. M. (1994), “Performance of Generalized Estimating Equations in Practical Situations,” Biometrics, 50, 270–278.
Lipsitz, S. H., Kim, K., and Zhao, L. (1994), “Analysis of Repeated Categorical Data Using Generalized Estimating Equations,” Statistics in Medicine, 13, 1149–1163.
Littell, R. C., Freund, R. J., and Spector, P. C. (1991), SAS System for Linear Models, Third Edition, Cary, NC: SAS Institute Inc.
Long, J. S. (1997), Regression Models for Categorical and Limited Dependent Variables, Thousand Oaks, CA: Sage Publications.
McCullagh, P. (1983), “Quasi-likelihood Functions,” Annals of Statistics, 11, 59–67.
McCullagh, P. and Nelder, J. A. (1989), Generalized Linear Models, Second Edition, London: Chapman & Hall.
Meeker, W. Q. and Escobar, L. A. (1998), Statistical Methods for Reliability Data, New York: John Wiley & Sons.
Mehta, C. R., Patel, N., and Senchaudhuri, P. (1992), “Exact Stratified Linear Rank Tests for Ordered Categorical and Binary Data,” Journal of Computational and Graphical Statistics, 1, 21–40.
Miller, M. E., Davis, C. S., and Landis, J. R. (1993), “The Analysis of Longitudinal Polytomous Data: Generalized Estimating Equations and Connections with Weighted Least Squares,” Biometrics, 49, 1033–1044.
Myers, R. H., Montgomery, D. C., and Vining, G. G. (2002), Generalized Linear Models with Applications in Engineering and the Sciences, New York: John Wiley & Sons.
Nelder, J. A. and Wedderburn, R. W. M. (1972), “Generalized Linear Models,” Journal of the Royal Statistical Society, Series A, 135, 370–384.
Nelson, W. (1982), Applied Life Data Analysis, New York: John Wiley & Sons.
Neter, J., Kutner, M. H., Nachtsheim, C. J., and Wasserman, W. (1996), Applied Linear Statistical Models, Fourth Edition, Chicago: Irwin.
Pan, W. (2001), “Akaike’s Information Criterion in Generalized Estimating Equations,” Biometrics, 57, 120–125.
Pregibon, D. (1981), “Logistic Regression Diagnostics,” Annals of Statistics, 9, 705–724.
Preisser, J. S. and Qaqish, B. F. (1996), “Deletion Diagnostics for Generalised Estimating Equations,” Biometrika, 83, 551–562.
Rao, C. R. (1973), Linear Statistical Inference and Its Applications, Second Edition, New York: John Wiley & Sons.
Rotnitzky, A. and Jewell, N. P. (1990), “Hypothesis Testing of Regression Parameters in Semiparametric Generalized Linear Models for Cluster Correlated Data,” Biometrika, 77, 485–497.
Royall, R. M. (1986), “Model Robust Inference Using Maximum Likelihood Estimators,” International Statistical Review, 54, 221–226.
Searle, S. R. (1971), Linear Models, New York: John Wiley & Sons.
Simonoff, J. S. (2003), Analyzing Categorical Data, New York: Springer-Verlag.
Spiegelhalter, D. J., Best, N. G., Carlin, B. P., and Van der Linde, A. (2002), “Bayesian Measures of Model Complexity and Fit,” Journal of the Royal Statistical Society, Series B, 64(4), 583–616, with discussion.
Stokes, M. E., Davis, C. S., and Koch, G. G. (2000), Categorical Data Analysis Using the SAS System, Second Edition, Cary, NC: SAS Institute Inc.
Thall, P. F. and Vail, S. C. (1990), “Some Covariance Models for Longitudinal Count Data with Overdispersion,” Biometrics, 46, 657–671.
Ware, J. H., Dockery, S. A. I., Speizer, F. E., and Ferris, B. G., Jr. (1984), “Passive Smoking, Gas Cooking, and Respiratory Health of Children Living in Six Cities,” American Review of Respiratory Diseases, 129, 366–374.
White, H. (1982), “Maximum Likelihood Estimation of Misspecified Models,” Econometrica, 50, 1–25.
Williams, D. A. (1987), “Generalized Linear Model Diagnostics Using the Deviance and Single Case Deletions,” Applied Statistics, 36, 181–191.
Zeger, S. L., Liang, K.-Y., and Albert, P. S. (1988), “Models for Longitudinal Data: A Generalized Estimating Equation Approach,” Biometrics, 44, 1049–1060.