參考文獻 |
Aalen O.O. (1992). Modelling heterogeneity in survival analysis by the compound Poisson distribution. Annals of Applied Probability, 2, 951-972.
Andersen P.K., Gill R.D. (1982). Cox’s regression model for counting processes: a large sample study. Annals of Statistics, 10(4), 1100-1120.
Balakrishnan N., Peng Y.W. (2006). Generalized gamma frailty model. Statistics in Medicine, 25, 2797-2816.
Bates D., Maechler M., Bollker B. (2012). lme4: Linear Mixed-Effects Models Using S4 Classes. R package version 0.999999-0, URL~http://cran.r-project.org/web/packages/lme4/.
Brown E.R., Ibrahim J.G., DeGruttola V. (2005). A Flexible B-spline Model for Multiple Longitudinal Biomarkers and Survival. Biometrics, 61, 64-73.
Bycott P., Taylor J. (1998). A Comparison of Smoothing Techniques for CD4 Data Measured with Error in a Time-Dependent Cox Proportional Hazards Model. Statist. Medicine, 17, 2061-2077.
Carey J.R., Liedo P., Muller H.G., Wang J.L., Chiou J.M. (1998). Relationship of Age Patterns of Fecundity to Mortality, Longevity, and Lifetime Reproduction in a Large Cohort of Mediterranean Fruit Fly Females. J. Gerontology: Biological Sciences, 53, 245-251.
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., Oakes D. (1984). Analysis of Survival Data. London: Chapman and Hall.
Ding J., Wang J.L. (2008). Modeling Longitudinal Data with Nonparametric Multiplicative Random Effects Jointly with Survival Data. Biometrics, 64, 546-556.
Fleming T.R., Harrington D.P. (1991). Counting Processes and Survival Analysis. Wiley, New York.
Gao X., Carlin B. (2004). Seperate and Joint Modeling of Longitudinal and Event Time Data Using Standard Computer Packages. The American Statistican, 58, 16-24.
Grambsch P.M., Therneau T.M. (1994). Proportional Hazards Tests and Diagnostics Based on Weighted Residuals. Biometrika, 81, 515-526.
Greenwood M., Yule G.U. (1920). An enquiry into the nature of frequency distributions representative of multiple happenings with particular reference of multiple attacks of disease or of repeated accidents. Journal of the Royal Statistical Society, 83, 255-279.
Heath M.T. (2002). Scientific Computing: An Introductory Survey. 2nd edition. McGraw-Hill.
Henderson R., Diggle P., Dobson A. (2000). Joint Modeling of Longitudinal Measurements and Event Time Data. Biostatistics, 4, 465-480.
Hsieh F.S., Tseng Y.K., Wang J.L. (2006). Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisted. Boimetrics, 62, 1037-1043.
Hougaard P. (1986). Survival models for heterogeneous populations derived from stable distributions. Biometrika, 73, 387-396.
Hougaard P. (1986). A class of multivariate failure time distributions. Biometrika, 73, 671-678.
Hougaard P. (2000). Analysis of Multivariate Survival Data. Springer: New York, 2000.
Hougaard P., Myglegaard P., Borch-Johnsen K. (1994). Heterogeneity models of disease susceptibility, with application to diabetic nephropathy. Biometrics, 50, 1178-1188.
The Performance of Kernel Density Functions in Kernel Distribution Function Estimation. Statistics & Probability Letters, 9, 129-132.
Using Non-stochastic Terms to Advantage in Kernel-based Estimation of Intergrated Squared Density Derivatives. Statistics & Probability Letters, 11, 511-514.
Generalized Cross-validation for Bandwidth Selection of Backfitting Estimates in Gerneralized Additive Models. Journal of Computational & Graphical Statistics, 13, 66-89.
Klein J.P. (1992). Semiparametric estimation of random effects using the Cox model based on EM algorithm. Biometrics, 48, 795-806.
Lam K.F., Kuk A.Y.C. (1997). A marginal likelihood approach to estimation in frailty models. Journal of the American Statistical Association, 92, 985-990.
Landers T.L., Jiang S.T., Peek J.R. (2001). Semi-parametric PWP model robustness for log-linear increasing rates of occurrence of failures. Reliab Eng Syst Saf, 73, 145-153.
Landers T.L., Soroudi H.E. (1991). Robustness of a semi-parametric proportional intensity model. IEEE Trans. Reliab., 40(2), 161-164.
Liao, J. G., We, Y., Lin Y. (2010). Improving Sheather and Jones’ bandwidth selector for difficult densities in kernel density estimation. Journal of nonparametric statistics, 22, 105-114.
Lim H.J., Liu J., Melzer-Lange M. (2007). Comparison of Methods for Analyzing Recurrent Events Data: Application to the Emergency Department Visits of Pediatric Firearm Victims. Acceident Analysis and Prevention, 39, 290-299.
Lin D.Y., Ying Z. (1995). Semiparametric inference for the accelerated life model with time-dependent covariates. Journal of Statistical Planning and Inference, 44, 47-63.
Liu L., Huang X. (2009). Joint analysis of correlated repeated measures and recurrent events processes in the presence of death, with application to a study on acquired immune deficiency syndrome. Journal of the Royal Statistical Society: Series C, 58, 65-81.
McGilchrist C.A. (1993). REML estimation for survival models with frailty. Biometrics, 49, 221-225.
Nielsen G.G., Gill R.D., Andersen P.K., Srensen T.I.A. (1992).
Counting process approach to maximum likelihood estimation in frailty models. Scandinavian Journal of Statistics, 19, 25-43.
Pan W. (2001). Using frailties in the accelerated failure time model. Lifetime Data Anal., 7(1), 55-64.
Pawitan Y., Self S. (1993). Modeling Disease Marker Processes in AIDS. J. Amer. Statist. Assoc., 83, 719-726.
Prentice R.L., Williams B.J., Peterson A.V. (1981). On the regression analysis of multivariate failure time data. Biometrika, 68, 373-379.
Qureshi W.M., Landers T.L., Edward E.G. (1994). Robustness evaluation of a semi-parametric proportional intensity model. Reliab. Eng. Syst. Saf., 44, 103-109.
R Development Core Team (2012). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-12-7, URL~http://www.R-project.org/.
Rizopoulos D. (2010).
JM: An R Package for the Joint Modelling of Longitudinal and Time-to-Event Data. Journal of Statistical Software, 35, 1-33.
Rizopoulos D. (2012). JM: Joint Modeling of Longitudinal and Survival Data. R package version 1.0-0, URL~http://cran.r-project.org/web/packages/JM/.
Rizopoulos, D., Verbeke, G., Molenberghs, G. (2008). Shared parameter models under random effects misspecification. Biometrka, 95, 63-74.
Robins J., Tsiatis A.A. (1992). Semiparametric Estimation of an Accelerated Failure Time Model with Time Dependent Covariates. Biometrika, 79, 311-319.
Sheather, Jones (1991). A reliable data-based bandwidth selection method for kernel density estimation. Journal of the Royal Statistical Society: Series B, 52, 683-690.
Song X., Davidian M., Tsiatis A.A. (2002). A Semiparametric Likelihood Approach to Joint Modelling of Longitudinal and Time-to-Event Data. Biometrics, 58, 742-753.
The MathWorks, Inc (2007). MATLAB: The Language of Technical Computing, Version 7.9.0. The MathWorks, Inc., Natick, Massachusetts. URL~http://www.mathworks.com/products/matlab/.
Therneau T. (2012). Survival: Survival Analysis, including Penalised Likelihood. R package version 2.36-14, URL~http://cran.r-project.org/web/packages/survival/.
Therneau T.M., Grambsch P.M. (2000). Modeling Survival Data: Extending the Cox Model. Springer-Verlag, New York.
Tseng Y.K., Hseih F.S., Wang J.L. (2005). Joint Modeling of Accelerated Failure Time and Longitudinal Data. Boimetrika, 92, 587-603.
Tsiatis A.A., 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., 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. J. Amer. Statist. Assoc., 90, 27-37.
Vaupel J.W., Manton K.G., and Stallard E. (1997). The impact of heterogeneity in individual frailty on the dynamics of mortality. Demography, 16, 439-454.
Verbeke G. and Davidian M. (2008). Joint Models for Longitudinal Data: Introduction and Overview. Longitudinal Data Analysis: Handbooks of Modern Statistical Methods Ed. Fitzmaurice, G, Davidian, M, Verbeke, G, Molenberghs, G, 319-326. Chapman & Hall/CRC.
Vithala S. (1994). Robustness of a semi-parametric proportional intensity model for the case of a log-linear non-homogeneous Poisson process. A thesis of the Industrial Engineering Department at the University of Arkansas.
Wang Y., 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.
Wei G.C.G., Tanner M.A. (1990). A Monte Carlo Implementation of the EM Algorithm and Poor Man’s Data Augmentation Algorithm. J. Amer. Statist. Assoc., 85, 699-704.
Wei, L.J., Lin, D.Y., Weissfeld, L. (1989). Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. Journal of the American Statistical Association, 84, 1065-1073.
Wulfsohn M.S., Tsiatis A.A. (1997). A Joint Model for Survival and Longitudinal Data Measured with Error. Boimetrics, 53, 330-339.
Xu L., Zhang J. (2010). An EM-like algorithm for the semiparametric accelerated failure time gamma frailty model. Computational Statistics and Data Analysis, 54, 1467-1474.
Yu M., Law N.J., Taylor J.M.G., Sandler H.M. (2004). Joint Longitudinal-Survival-Cure Models and their Application to Prostate Cancer. Statistica Sinica, 14, 835-862.
Zeng D., Cai J. (2005). Asymptotic Results for Maximum Likelihood Estimators in Joint Analysis of Repeated Measurements and Survival Time. Ann. Stat., 33, 2132-2163.
Zeng D. and Lin, D.Y. (2007). Efficient Estimation in the Accelerated Failure Time Model. Journal of the American Statistical Association, 102, 1387-1396.
Zhang J., Peng Y. (2007). An alternative estimation method for the accelerated failure time frailty model. Comput. Statist. Data Anal., 51(9), 4413-4423. |