References
- Andersen PK, Gill RD. Cox's regression model for counting processes: a large sample study. Ann Statist. 1982;10:1100–1120.
- Prentice RL, Williams BJ, Peterson AV. On the regression analysis of multivariate failure time data. Biometrika. 1981;68:373–379.
- Wei L-J, Lin DY, Weissfeld L. Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. J Am Stat Assoc. 1989;84:1065–1073.
- Duffield-Lillico AJ, Reid ME, Turnbull BW, et al. Baseline characteristics and the effect of selenium supplementation on cancer incidence in a randomized clinical trial: a summary report of the nutritional prevention of cancer trial. Cancer Epidemiol Prev Biomar. 2002;11:630–639.
- Duffield-Lillico AJ, Slate EH, Reid ME, et al. Selenium supplementation and secondary prevention of nonmelanoma skin cancer in a randomized trial. J Natl Cancer Inst. 2003;95:1477–1481.
- Bedair K, Hong Y, Li J, et al. Multivariate frailty models for multi-type recurrent event data and its application to cancer prevention trial. Comput Stat Data Anal. 2016;101:161–173.
- Lin L-A, Luo S, Chen BE, et al. Bayesian analysis of multi-type recurrent events and dependent termination with nonparametric covariate functions. Stat Methods Med Res. 2017;26:2869–2884.
- Zeng D, Ibrahim JG, Chen M-H, et al. Multivariate recurrent events in the presence of multivariate informative censoring with applications to bleeding and transfusion events in myelodysplastic syndrome. J Biopharm Stat. 2014;24:429–442.
- Duchateau L, Janssen P. The frailty model. New York: Springer; 2008.
- Shih JH, Louis TA. Inferences on the association parameter in copula models for bivariate survival data. Biometrics. 1995;51:1384–1399.
- Chatterjee M, Roy SS. A copula-based approach for estimating the survival functions of two alternating recurrent events. J Stat Comput Simul. 2018;88:3098–3115.
- Tawiah R, McLachlan GJ, Ng SK. A bivariate joint frailty model with mixture framework for survival analysis of recurrent events with dependent censoring and cure fraction. Biometrics. 2020;76:753–766.
- Rondeau V, Mathoulin-Pelissier S, Jacqmin-Gadda H, et al. Joint frailty models for recurring events and death using maximum penalized likelihood estimation: application on cancer events. Biostatistics. 2007;8:708–721.
- Mazroui Y, Mauguen A, Mathoulin-Pélissier S, et al. Time-varying coefficients in a multivariate frailty model: application to breast cancer recurrences of several types and death. Lifetime Data Anal. 2016;22:1–25.
- Li Q, Guo F, Kim I. A non-parametric Bayesian change-point method for recurrent events. J Stat Comput Simul. 2020;90:2929–2948.
- Cook RJ, Lawless JF, Lee K-A. A copula-based mixed Poisson model for bivariate recurrent events under event-dependent censoring. Stat Med. 2010;29:694–707.
- Liu L, Huang X. The use of Gaussian quadrature for estimation in frailty proportional hazards models. Stat Med. 2008;27:2665–2683.
- Lee J, Cook RJ. Dependence modeling for multi-type recurrent events via copulas. Stat Med. 2019;38:4066–4082.
- Nelsen RB. An introduction to copulas. New York: Springer; 1999.
- Booth JG, Hobert JP. Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm. J R Stat Soc Ser B (Stat Methodol). 1999;61:265–285.
- Joe H. Asymptotic efficiency of the two-stage estimation method for copula-based models. J Multivar Anal. 2005;94:401–419.
- Joe H, Xu JJ. The estimation method of inference functions for margins for multivariate models. University of British Columbia; 1996. (Technical report). DOI:https://doi.org/10.14288/1.0225985
- Louis TA. Finding the observed information matrix when using the EM algorithm. J R Stat Soc Ser B (Methodol). 1982;22:226–233.
- Parner E. Asymptotic theory for the correlated gamma-frailty model. Ann Statist. 1998;26:183–214.
- Therneau TM, Grambsch PM. Modeling survival data: extending the Cox model. New York: Springer; 2000.