References

Andersen, P. K., Borgan, ˜., 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 “47.

Breslow, N. E. (1974), Covariance Analysis of Censored Survival Data, Biometrics , 30, 89 “99.

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.

Fleming, T. R. and Harrington, D. (1991), Counting Processes and Survival Analysis , New York: John Wiley & Sons, Inc.

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.

Grambsch, P. M. and Therneau, T. M. (1994), Proportional Hazards Tests and Diagnostics Based on Weighted Residuals, Biometrika , 81, 515 “526.

Hosmer, D. W. J. and Lemeshow, S. (1989), Applied Logistic Regression , New York: John Wiley & Sons, Inc.

Kalbfleisch, J. D. and Prentice, R. L. (1980), The Statistical Analysis of Failure Time Data , New York: John Wiley & Sons, Inc.

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. and Nadeau, C. (1995), Some Simple Robust Methods for the Analysis of Recurrent Events, Technometrics , 37, 158 “168.

Lee, E., Wei, L., and Amato, D. (1992), Cox-Type Regression Analysis for Large Numbers of Small Groups of Correlated Failure Time Observations, 237 “247, Netherlands: Kluwer Academic Publishers.

Lin, D. (1994), Cox Regression Analysis of Multivariate Failure Time Data: The Marginal Approach, Statistics in Medicine , 13, 2233 “2247.

Lin, D., Wei, L., 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., Wei, L., and Ying, Z. (1993), Checking the Cox Model with Cumulative Sums of Martingale-Based Residuals, Biometrika , 80, 557 “572.

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.

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. 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 Cr peau, H. (1985), Influence Functions for Proportional Hazards Regression, Biometrika , 72, 1 “9.

Schoenfeld, D. (1982), Partial Residuals for the Proportional Hazards Regression Model, Biometrika , 69, 239 “241.

Therneau, T. M. and Grambsch, P. M. (2000), Modeling Survival Data: Extending the Cox Model , New York: Springer-Verlag.

Therneau, T. M., Grambsch, P. M., and Fleming, T. R. (1990), Martingale-Based Residuals and Survival Models, Biometrika , 77, 147 “160.

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.

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.