參考文獻 |
Abrahamowicz, M., Mackenzie, T. and Esdaile, J. M. (1996).“Time-Dependent Hazard Ratio : Modeling and Hypothesis Testing with Application in Lupus Nephritis.”Journal of the American Statistical Association, 91, 1432-1439.
Andersen, P. K., Borgan, Ø., Gill, R. D. and Keiding, N. (1993). Statistical Models Based on Counting Processes. Springer, New York.
Andersen, P. K. and Gill, R. D. (1982).“Cox’s Regression Model for Counting Processes : A Large Sample Study.” The Annals of Statistics, 10, 1100-1120.
Cox, D. R. (1972).“Regression Models and Life Tables (with Discussion).”Journal of
the Royal Statistical Society, Series B, 34, 187-220.
Cox, D. R. and Oakes, D. (1984). Analysis of Survival Data. London : Chapman and Hall.
Etezadi-Amoli, J. and Ciampi, A. (1987).“Extended Hazard Regression for Censored Survival Data with Covariates : A Spline Approximation for The Baseline Hazard Function.”Biometrics, 43, 181-192.
Grambsch, P. M. and Therneau, T. M. (1994).“Proportional Hazards Tests and Diagnostics Based on Weighted Residuals.”Biometrics, 81, 515-526.
Jiang, L., Zhang, D. and Davidian, M. (2006).“Smoothing Spline-Based Score Tests for Proportional Hazards Models.” Biometrics, 62, 803-812.
Kauermann, G. and Berger, U. (2003).“A Smooth Test in Proportional Hazard Survival Models Using Local Partial Likelihood Fitting.”Lifetime Data Analysis, 9, 373-393.
Kraus, D. (2007a).“Data-Driven Smooth Tests of The Proportional Hazards Assumption.” Lifetime Data Analysis, 13, 1-16.
Kraus, D. (2007b). Neyman's Smooth Tests in Survival Analysis. PhD thesis. Charles University in Prague, Department of Statistics.
Kraus, D. (2008).“Identifying Nonproportional Covariates in The Cox Model. Communications in Statistics. Theory Methods, 37, 617-625.
Laird, N. M. and Ware, J. H. (1982).“Random-Effects Models for Longitudinal Data.” Biometrics, 38, 963-974.
Ledwina, T. (1994).“Data-Driven Version of Neyman’s Smooth Test of Fit.”Journal of the American Statistical Association, 89, 1000-1005.
Lin, D. Y., Wei, L. J. and Ying, Z. (1993).“Checking The Cox Model with Cumulative Sums of Martingale-Based Residuals.”Biometrika, 80, 3, 557-572.
Marzec, L. and Marzec, P. (1997).“Generalized Martingale-Residual Processes for Goodness-of-Fit Inference in Cox's Type Regression Models.” The Annals of Statistics, 25, 683-714.
Miller, R. G. (1981). Survival Analysis. Wiley: New York.
Pawitan, Y. and Self, S. (1993).“Modeling Disease Marker Processes in AIDS.”Journal of the American Statistical Association, 88, 719-726.
Pena, E. A. (2003).“Classes of Fixed-Order and Adaptive Smooth Goodness-of-Fit Tests with Discrete Right-Censored Data.” In: Mathematical and Statistical Methods in Reliability (Trondheim, 2002). World Science Publishing, River Edge.
Prentice, R. L. (1982). “Covariate Measurement Errors and Parameter Estimation in A Failure Time Regression Model.”Biometrika, 69, 331-342.
Schoenfeld, D. (1982).“Partial Residuals for The Proportional Hazards Regression Model.” Biometrika, 69, 239-241.
Therneau, T. M., Grambsch, P. M. and Fleming, T. R. (1990).“Martingale-Based Residuals for Survival Models.”Biometrika, 77, 147-160.
Tsiatis, A. A., Degruttola, V. and Wulfsohn, M. S. (1995).“Modeling The Relationship of Survival to Longitudinal Data Measured With Error. Applications to Survival and CD4 Counts in Patients with AIDS.”Journal of the American Statistical Association, 90, 27-37.
Wang, Y. and Taylor, J. M. G. (2001).“ Jointly Modeling Longitudinal and Event Time Data with Application to Acquired Immunodeficiency Syndrome.” Journal of the American Statistical Association, 96, 895-905.
Wulfsohn, M. S. and Tsiatis, A. A. (1997).“A Joint Model for Survival and Longitudinal Data Measured with Error.”Biometrics, 53, 330-339.
Zeng, D. and Cai, J. (2005).“Asymptotic Results for Maximum Likelihood Estimators In Joint Analysis of Repeated Measurements and Survival Time.”The Annals of Statistics, 33(5), 2132-2163.
|