參考文獻 |
Ciampi, A. and Etezadi-Amoli, J. (1985). “A general model for testing the proportional hazards and the accelerated failure time hypothesis in the analysis of censored survival data with covariate.” Communications in Statistics, 14, 651-667.
Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society, 34, 187-220.
Cox, D. R. and Oakes, D. (1984), Analysis of Survival Data, Chapman and Hall, London, New York.
Dafni, U. G. and Tsiatis, A. A. (1998). Evaluating Surrogate Markers of Clinical Outcome When Measured with Error. Biometrics, 54, 1445-1462.
Dubin, J. A., Müller, H. G. and Wang, J. L. (2001). Event history graphs for censored survival data. Statistics in Medicine, 20, 2951-2964.
Efron, B., Tibshirani, R. J. (1993). An introduction to the Bootstrap. Chapman & Hall, New York.
Henderson, R., Diggle, P. and Dobson, A. (2000). Joint modeling of longitudinal measurements and event time data. Biostatistics, 4, 465-480.
Hsieh, F., Tseng, Y. K. and Wang, J. L. (2006). Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisited. Biometrics, 62, 1037-1043.
John M. Kirkwood, Joseph Ibrahim, David H. Lawson, Michael B. Atkins, Sanjiv S. Agarwala, Keirsten Collins, Ruth Mascari, Donna M. Morrissey, Paul B. Chapman, High-Dose Interferon Alfa - 2b Does Not Diminish Antibody Response to GM2 Vaccination in Patients With Resected Melanoma: Results of the Multicenter Eastern Cooperative Oncology Group Phase II Trial E2696, Journal of Clinical Oncology, vol. 19, no. 5, 2001, pp. 1430-1436.
Jones, M.C. (1990). The performance of kernel density functions in kernel distribution
function estimation. Statistics and Probability Letters, 9, 129-132.
Jones, M.C. and Sheather, S.J. (1991). Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives. Statistics and Probability Letters, 11, 511-514.
Kaplan, E. L. and Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53, 457-481.
Laird, N. M. and Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38, 963-974.
Prentice, R. L. (1982). Covariate measurement errors and parameter estimation in a failure time regression model. Biometrika, 69, 331-342.
Schoenfeld, D. (1980). “Chi-Squared Goodness-of-Fit Tests for the Proportional Hazards Regression Model.” Biometrika, 67, 145-153.
Schoenfeld, D.A. (1982). “Partial residuals for the proportional hazards regression model.” Biometrika, 69, 239-241.
Tseng, Y. K., Hsieh F. and Wang, J. L. (2005). Joint modeling of accelerated failure time and longitudinal data. Biometrika, 92, 587-603.
Tsiatis, A. A. and Davidian, M. (2001). A semiparametric estimator for the proportional hazards model with longitudinal covariates measured with error. Biometrika, 88, 447-458.
Tsiatis, A. A. and Davidian, M. (2004). Joint Modeling of Longitudinal and Time-to-Event Data: An Overview. Statistica Sinica, 14, 809-834.
Tsiatis, A. A., DeGruttola, V. andWulfsohn, 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.
Zeng, D. and Lin, D. Y. (2007a). Maximum Likelihood Estimation in Semiparametric Regression Models with Censored Data (with Discussion). Journal of the Royal Statistical Society, Series B 69, 507-564.
Zeng, D. and Lin, D. Y. (2007b). Efficient Estimation in the Accelerated Failure Time Model. Journal of the American Statistical Association, 102, 1387-1396.
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