J. Amdahl. flexsurvcure: Flexible Parametric Cure Models, 2019. URL https://CRAN.R-project.org/ package=flexsurvcure. R package version 1.0.0. [p117]
M. Amico and I. Van Keilegom. Cure models in survival analysis. Annual Review of Statistics and Its Application, 5(1):311-342, 2018. URL https://doi.org/10.1146/annurev-statistics-031017-100101. [p116]
A. Beger, D. Chiba, D. W. Hill, Jr., N. W. Metternich, S. Minhas, and M. D. Ward. spduration: Split-Population Duration (Cure) Regression, 2018. URL https://CRAN.R-project.org/package= spduration. R package version 0.17.1. [p117]
A. Beretta and C. Heuchenne. Variable selection in proportional hazards cure model with time-varying covariates, application to us bank failures. Journal of Applied Statistics, 46(9):1529-1549, 2019a. URL https://doi.org/10.1080/02664763.2018.1554627. [p116, 118, 127]
A. Beretta and C. Heuchenne. penPHcure: Variable Selection in PH Cure Model with Time-Varying Covariates, 2019b. URL https://CRAN.R-project.org/package=penPHcure. R package version 1.0.2. [p116]
J. Berkson and R. P. Gage. Survival curve for cancer patients following treatment. Journal of the American Statistical Association, 47(259):501-515, 1952. URL https://doi.org/10.2307/2281318. [p116]
J. W. Boag. Maximum likelihood estimates of the proportion of patients cured by cancer therapy. Journal of the Royal Statistical Society: Series B (Methodological), 11(1):15-44, 1949. URL https://doi. org/10.1111/j.2517-6161.1949.tb00020.x. [p116]
N. Breslow. Covariance analysis of censored survival data. Biometrics, 30(1):89-99, 1974. URL https://doi.org/10.2307/2529620. [p118]
C. Cai, Y. Zou, Y. Peng, and J. Zhang. smcure: Fit Semiparametric Mixture Cure Models, 2012. URL https://CRAN.R-project.org/package=smcure. R package version 2.0. [p117]
R. A. Cole and J. W. Gunther. Separating the likelihood and timing of bank failure. Journal of Banking & Finance, 19(6):1073 - 1089,1995. URL https://doi.org/10.1016/0378- 4266(95)98952-M. [p116]
D. R. Cox. Regression models and life-tables. Journal of the Royal Statistical Society. Series B (Methodologi-cal),34(2):187-220,1972.URLhttps://doi.org/10.2307/2985181.[p116]
A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the em algorithm. Journal of the Royal Statistical Society. Series B (Methodological), 39(1):1-38, 1977. URL https://doi.org/10.1111/j.2517-6161.1977.tb01600.x.[p117]
B. Efron. The efficiency of cox's likelihood function for censored data. Journal of the American Statis-ticalAssociation,72(359):557-565,1977.URLhttps://doi.org/10.1080/01621459.1977.10480613. [p118]
J. Fan and R. Li. Variable selection via nonconcave penalized likelihood and its oracle properties. Journal of the American Statistical Association, 96(456):1348-1360, 2001. URL https://doi.org/10. 1198/016214501753382273. [p118, 119]
J. Fan and R. Li. Variable selection for cox's proportional hazards model and frailty model. Annals of Statistics, 30(1):74-99, 2002. URL https: //doi. org/1 0. 1 21 4/aos/1 01 53621 85. [p118]
J. Fox and M. Carvalho. The rcmdrplugin.survival package: Extending the r commander interface to survival analysis. Journal of Statistical Software, Articles, 49(7):1-32, 2012. URLhttps://doi.org/10. 18637/jss.v049.i07. [p122]
G. Garibotti, A. Tsodikov, and M. Clements. nltm: Non-Linear Transformation Models, 2019. URL https: //CRAN.R-project. org/package=nltm. R package version 1.4.2. [p117]
D. Hendry. Data generation for the cox proportional hazards model with time-dependent covariates: a method for medical researchers. Statistics in medicine, 33:436-454, 2014. URL https://doi.org/ 10.1002/sim.5945. [p116, 119]
D. R. Hunter and R. Li. Variable selection using mm algorithms. The Annals of Statistics, 33(4):1617-1642, 082005.URLhttps://doi.org/10.1214/009053605000000200.[p119]
C. Jackson. flexsurv: A platform for parametric survival modeling in R. Journal of Statistical Software, 70(8):1-33,2016.URLhttps://doi.org/10.18637/jss.v070.i08.[p117]
W. Q. Meeker. Limited failure population life tests: Application to integrated circuit reliability. Technometrics,29(1):51-65,1987.URLhttps://doi.org/10.1080/00401706.1987.10488183.[p116]
Y. Polo, F. J. Sese, and P. C. Verhoef. The effect of pricing and advertising on customer retention in a liberalizing market. Journal of Interactive Marketing, 25(4):201 - 214, 2011. URLhttps://doi.org/10. 1016/j.intmar.2011.02.002.[p116]
P. H. Rossi, R. A. Berk, and K. J. Lenihan. 2 - historical background of the transitional aid research project experiments. In P. H. Rossi, R. A. Berk, and K. J. Lenihan, editors, Money, Work, and Crime, pages 21 - 46. Academic Press, 1980. URL h ttps: //do i. o rg/ 1 0. 1 0 1 6/B9 7 8 - 0 - 1 2 - 5 98 240 - 5. 50009 - 0. [p122]
P. Schmidt and A. D. Witte. Predicting criminal recidivism using ‘split population' survival time models. Journal of Econometrics, 40(1):141-159,1989. URL https://doi.org/10.1016/0304-4076(89)90034- 1. [p116]
M. Svolik. Authoritarian reversals and democratic consolidation. American Political Science Review, 102 (2):153-168, 2008. URLhttps://doi.org/10.1017/S0003055408080143. [p116]
J. P. Sy and J. M. G. Taylor. Estimation in a cox proportional hazards cure model. Biometrics, 56(1): 227-236, 2000. URLhttps://doi.org/10.1111/j.0006-341X.2000.00227.x.[p116,127]
T. M. Therneau. A Package for Survival Analysis in S, 2015. URL https://CRAN.R-project.org/ package=survival. version 2.38. [p120]
E. N. Tong, C. Mues, and L. C. Thomas. Mixture cure models in credit scoring: If and when borrowers default. European Journal of Operational Research, 218(1):132-139, 2012. URL https://doi.org/10. 1016/j.ejor.2011.10.007. [p116]
A. Tsodikov. Semiparametric models: a generalized self-consistency approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 65(3):759-774, 2003. URL https://doi.org/10. 1 1 1 1 / 1 467-9868. 0041 4. [p117]
A. D. Tsodikov, J. G. Ibrahim, and A. Y. Yakovlev. Estimating cure rates from survival data: An alternative to two-component mixture models. Journal of the American Statistical Association, 98(464): 1063-1078,2003. URL https://doi.org/10.1198/01622145030000001007. [p11]
