|The PHREG Procedure|
Andersen, P. K., Borgan, O., Gill, R. D., and Keiding, N. (1992), Statistical Models Based on Counting Processes, New York: Springer-Verlag.
Andersen, P. K. and Gill, R. D. (1982), “Cox’s Regression Model Counting Process: A Large Sample Study,” Annals of Statistics, 10, 1100–1120.
Binder, D. A. (1992), “Fitting Cox’s Proportional Hazards Models from Survey Data,” Biometrika, 79, 139–147.
Breslow, N. E. (1972), “Discussion of Professor Cox’s Paper,” J. Royal Stat. Soc. B, 34, 216–217.
Breslow, N. E. (1974), “Covariance Analysis of Censored Survival Data,” Biometrics, 30, 89–99.
Bryson, M. C. and Johnson, M. E. (1981), “The Incidence of Monotone Likelihood in the Cox Model,” Technometrics, 23(4), 381–383.
Cain, K. C. and Lange, N. T. (1984), “Approximate Case Influence for the Proportional Hazards Regression Model with Censored Data,” Biometrics, 40, 493–499.
Cox, D. R. (1972), “Regression Models and Life Tables,” Journal of the Royal Statistical Society, Series B, 20, 187–220, with discussion.
Cox, D. R. (1975), “Partial Likelihood,” Biometrika, 62, 269–276.
Crowley, J. and Hu, M. (1977), “Covariance Analysis of Heart Transplant Survival Data,” Journal of the American Statistical Association, 72, 27–36.
DeLong, D. M., Guirguis, G. H., and So, Y. C. (1994), “Efficient Computation of Subset Selection Probabilities with Application to Cox Regression,” Biometrika, 81, 607–611.
Efron, B. (1977), “The Efficiency of Cox’s Likelihood Function for Censored Data,” Journal of the American Statistical Association, 72, 557–565.
Firth, D. (1993), “Bias Reduction of Maximum Likelihood Estimates,” Biometrika, 80, 27–38.
Fleming, T. R. and Harrington, D. (1991), Counting Processes and Survival Analysis, New York: John Wiley & Sons.
Furnival, G. M. and Wilson, R. W. (1974), “Regression by Leaps and Bounds,” Technometrics, 16, 499–511.
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.
Gilks, W. R., Best, N. G., and Tan, K. K. C. (1995), “Adaptive Rejection Metropolis Sampling with Gibbs Sampling,” Applied Statistics, 44, 455–472.
Grambsch, P. M. and Therneau, T. M. (1994), “Proportional Hazards Tests and Diagnostics Based on Weighted Residuals,” Biometrika, 81, 515–526.
Heinze, G. (1999), The Application of Firth’s Procedure to Cox and Logistic Regression, Technical Report 10/1999, update in January 2001, Section of Clinical Biometrics, Department of Medical Computer Sciences, University of Vienna.
Heinze, G. and Schemper, M. (2001), “A Solution to the Problem of Monotone Likelihood in Cox Regression,” Biometrics, 51, 114–119.
Hosmer, D. W., Jr. and Lemeshow, S. (1989), Applied Logistic Regression, New York: John Wiley & Sons.
Ibrahim, J. G., Chen, M. H., and Sinha, D. (2001), Bayesian Survival Analysis, New York: Springer-Verlag.
Kalbfleisch, J. D. and Prentice, R. L. (1980), The Statistical Analysis of Failure Time Data, New York: John Wiley & Sons.
Kass, R. E., Carlin, B. P., Gelman, A., and Neal, R. (1998), “Markov Chain Monte Carlo in Practice: A Roundtable Discussion,” The American Statistician, 52, 93–100.
Krall, J. M., Uthoff, V. A., and Harley, J. B. (1975), “A Step-up Procedure for Selecting Variables Associated with Survival,” Biometrics, 31, 49–57.
Lawless, J. F. (2003), Statistical Model and Methods for Lifetime Data, Second Edition, New York: John Wiley & Sons.
Lawless, J. F. and Nadeau, C. (1995), “Some Simple Robust Methods for the Analysis of Recurrent Events,” Technometrics, 37, 158–168.
Lee, E. W., Wei, L. J., and Amato, D. (1992), “Cox-Type Regression Analysis for Large Numbers of Small Groups of Correlated Failure Time Observations,” 237–247, Netherlands: Kluwer Academic.
Lin, D. Y. (1994), “Cox Regression Analysis of Multivariate Failure Time Data: The Marginal Approach,” Statistics in Medicine, 13, 2233–2247.
Lin, D. Y. and Wei, L. J. (1989), “The Robust Inference for the Proportional Hazards Model,” Journal of the American Statistical Association, 84, 1074–1078.
Lin, D. Y., Wei, L. J., Yang, I., and Ying, Z. (2000), “Semiparametric Regression for the Mean and Rate Functions of Recurrent Events,” Journal of the Royal Statistical Society, Series B, 62, 711–730.
Lin, D. Y., Wei, L. J., and Ying, Z. (1993), “Checking the Cox Model with Cumulative Sums of Martingale-Based Residuals,” Biometrika, 80, 557–572.
Nelson, W. (2002), Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications, ASA-SIAM Series on Statistics and Applied Probability.
Pepe, M. S. and Cai, J. (1993), “Some Graphical Displays and Marginal Regression Analyses for Recurrent Failure Times and Time Dependent Covariates,” Journal of the American Statistical Association, 88, 881–820.
Pettitt, A. N. and Bin Daud, I. (1989), “Case-Weighted Measures of Influence for Proportional Hazards Regression,” Applied Statistics, 38, 313–329.
Prentice, R. L., Williams, B. J., and Peterson, A. V. (1981), “On the Regression Analysis of Multivariate Failure Time Data,” Biometrika, 68, 373–379.
Reid, N. and Crèpeau, H. (1985), “Influence Functions for Proportional Hazards Regression,” Biometrika, 72, 1–9.
Sinha, D., Ibrahim, J. G., and Chen, M. H. (2003), “A Bayesian Justification of Cox’s Partial Likelihood,” Biometrika, 90, 629–641.
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.
Spiekerman, C. F. and Lin, D. Y. (1998), “Marginal Regression Models for Multivariate Failure Time Data,” Journal of American Statistical Association, 93, 1164–1175.
Therneau, T. M. (1994), A Package for Survival Analysis in S, Technical Report 53, Section of Biostatistics, Mayo Clinic, Rochester, MN.
Therneau, T. M. and Grambsch, P. M. (2000), Modeling Survival Data: Extending the Cox Model, New York: Springer-Verlag.
Tsiatis, A. (1981), “A Large Sample Study of the Estimates for the Integrated Hazard Function in Cox’s Regression Model for Survival Data,” Annals of Statistics, 9, 93–108.
Venzon, D. J. and Moolgavkar, S. H. (1988), “A Method for Computing Profile-Likelihood Based Confidence Intervals,” Applied Statistics, 37, 87–94.
Wei, L. J., Lin, D. Y., and Weissfeld, L. (1989), “Regression Analysis of Multivariate Incomplete Failure Time Data by Modeling Marginal Distribution,” Journal of the American Statistical Association, 84, 1065–1073.
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