Multiple event times in the presence of informative censoring: modeling and analysis by copulas
暂无分享,去创建一个
Dongdong Li | X Joan Hu | Mary L McBride | John J Spinelli | J. Spinelli | M. McBride | X. J. Hu | Dongdong Li | X. Joan Hu | Mary L. McBride | John J. Spinelli
[1] Stephen W. Lagakos,et al. Interim analyses using repeated confidence bands , 1999 .
[2] Satoshi Morita,et al. Disease-free survival as a surrogate for overall survival in adjuvant trials of gastric cancer: a meta-analysis. , 2013, Journal of the National Cancer Institute.
[3] Per Kragh Andersen,et al. Life years lost among patients with a given disease , 2017, Statistics in medicine.
[4] Michael R. Kosorok,et al. Pseudo Self‐Consistent Estimation of a Copula Model with Informative Censoring , 2005 .
[5] Yu Cheng,et al. Cumulative incidence association models for bivariate competing risks data , 2012, Journal of the Royal Statistical Society. Series B, Statistical methodology.
[6] Jing Ning,et al. Estimation of time‐dependent association for bivariate failure times in the presence of a competing risk , 2014, Biometrics.
[7] P. J. Huber. The behavior of maximum likelihood estimates under nonstandard conditions , 1967 .
[8] John P. Klein,et al. Estimates of marginal survival for dependent competing risks based on an assumed copula , 1995 .
[9] Niels Keiding,et al. Statistical Models Based on Counting Processes , 1993 .
[10] D. Clayton. A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence , 1978 .
[11] S W Lagakos,et al. Use of the Wei-Lin-Weissfeld method for the analysis of a recurring and a terminating event. , 1997, Statistics in medicine.
[12] Jerald F. Lawless,et al. Comparison of semiparametric maximum likelihood estimation and two-stage semiparametric estimation in copula models , 2011, Comput. Stat. Data Anal..
[13] Dongdong Li,et al. Statistical inference using large administrative data on multiple event times, with application to cancer survivorship research , 2018 .
[14] Zhe Zhang,et al. Comparison of breast cancer recurrence risk and cardiovascular disease incidence risk among postmenopausal women with breast cancer , 2012, Breast Cancer Research and Treatment.
[15] T. Louis,et al. Inferences on the association parameter in copula models for bivariate survival data. , 1995, Biometrics.
[16] Karen Bandeen-Roche,et al. Modelling multivariate failure time associations in the presence of a competing risk , 2002 .
[17] Paul Janssen,et al. Frailty models and copulas: similarities and differences , 2008 .
[18] Jason P. Fine,et al. On semi-competing risks data , 2001 .
[19] Scott Tyldesley,et al. Second malignancies after adjuvant radiation therapy for early stage breast cancer: is there increased risk with addition of regional radiation to local radiation? , 2015, International journal of radiation oncology, biology, physics.
[20] Marius Hofert,et al. Nested Archimedean Copulas Meet R: The nacopula Package , 2011 .
[21] Yujie Zhong,et al. Augmented composite likelihood for copula modeling in family studies under biased sampling. , 2016, Biostatistics.
[22] Yu Cheng,et al. Nonparametric Association Analysis of Bivariate Competing-Risks Data , 2007 .
[23] Kathryn Chaloner,et al. A copula model for bivariate hybrid censored survival data with application to the MACS study , 2010, Lifetime data analysis.
[24] Jun Yan,et al. Modeling Multivariate Distributions with Continuous Margins Using the copula R Package , 2010 .
[25] H. Joe. Multivariate Models and Multivariate Dependence Concepts , 1997 .
[26] J. Qin,et al. Semiparametric Analysis for Recurrent Event Data with Time‐Dependent Covariates and Informative Censoring , 2010, Biometrics.
[27] D. Oakes. Multivariate survival distributions , 1994 .
[28] Christopher Baliski,et al. HOSPITAL-RELATED CARDIAC MORBIDITY AMONG SURVIVORS OF BREAST CANCER: LONG-TERM RISKS AND PREDICTORS , 2014 .
[29] C. Genest,et al. A semiparametric estimation procedure of dependence parameters in multivariate families of distributions , 1995 .
[30] R. Nelsen. An Introduction to Copulas , 1998 .
[31] D. Oakes,et al. Bivariate survival models induced by frailties , 1989 .
[32] Mary L McBride,et al. Analysis of counts with two latent classes, with application to risk assessment based on physician-visit records of cancer survivors. , 2014, Biostatistics.
[33] Yi Li,et al. Mixture cure survival models with dependent censoring , 2007 .
[34] Richard D Riley,et al. An alternative pseudolikelihood method for multivariate random-effects meta-analysis , 2014, Statistics in medicine.
[35] Scott L. Zeger,et al. Some recent developments for regression analysis of multivariate failure time data , 1995, Lifetime data analysis.
[36] Jun Yan,et al. Enjoy the Joy of Copulas: With a Package copula , 2007 .
[37] Richard J Cook,et al. Composite likelihood for joint analysis of multiple multistate processes via copulas. , 2014, Biostatistics.
[38] Randi Foraker,et al. Cardiovascular disease and mortality after breast cancer in postmenopausal women: Results from the Women’s Health Initiative , 2017, PloS one.
[39] P. Andersen,et al. Decomposition of number of life years lost according to causes of death , 2013, Statistics in medicine.
[40] Weijing Wang,et al. Estimating the association parameter for copula models under dependent censoring , 2003 .
[41] Lihui Zhao,et al. Statistical monitoring of clinical trials with multivariate response and/or multiple arms: a flexible approach. , 2009, Biostatistics.
[42] B. Tom,et al. The versatility of multi-state models for the analysis of longitudinal data with unobservable features , 2012, Lifetime Data Analysis.
[43] Jinfeng Xu,et al. Statistical Analysis of Illness–Death Processes and Semicompeting Risks Data , 2010, Biometrics.
[44] R. Serfling. Approximation Theorems of Mathematical Statistics , 1980 .