References
- Balakrishnan, N., Pal, S. (2012). EM algorithm-based likelihood estimation for some cure rate models. J. Statist. Theor. Practice 6:698–724.
- Balakrishnan, N., Peng, Y. (2006). Generalized gamma frailty model. Statist. Med. 25:2797–2816.
- Berkson, J., Gage, R.P. (1952). Survival cure for cancer patients following treatment. J. Amer. Statist. Assoc. 47:501–515.
- Boag, J.W. (1949). Maximum likelihood estimates of the proportion of patients cured by cancer therapy. J. Roy. Statist. Soc. Ser. B 11:15–53.
- Cox, D., Oakes, D. (1984). Analysis of Survival Data. London: Chapman & Hall.
- Chen, M.-H., Ibrahim, J.G., Sinha, D. (1999). A new Bayesian model for survival data with a surviving fraction. J. Amer. Statist. Assoc. 94:909–919.
- Claeskens, G., Nguti, R., Janssen, P. (2008). One-sided tests in shared frailty models. Test 17:69–82.
- Conway, R.W., Maxwell, W.L. (1961). A queuing model with state dependent services rates. J. Industr. Eng. XII:132–136.
- Dempster, A.P., Laird, N.M., Rubin, D.B. (1977). Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Statist. Soc. Ser. B 39:1–38.
- Farewell, V.T. (1982). The use of mixture models for the analysis of survival data with long-term survivors. Biometrics 38:1041–1046.
- Hoggart, C.J., Griffin, J.E. (2001). A Bayesian partition model for customer attrition. In: George, E.I., Ed., Bayesian Methods with Applications to Science, Policy, and Official Statistics (Selected Papers from ISBA 2000), Proc. of the Sixth World Meeting of the International Society for Bayesian Analysis. International Society for Bayesian Analysis, Creta, Greece, pp. 61–70.
- Ibrahim, J.G., Chen, M.-H., Sinha, D. (2001). Bayesian Survival Analysis. New York: Springer-Verlag.
- Kadane, J.B., Shmueli, G., Minka, T.P., Borle, S., Boatwright, P. (2006). Conjugate analysis of the Conway-Maxwell-Poisson distribution. Bayesian Anal. 1:363–374.
- Klebanov, L.B., Rachev, S.T., Yakovlev, A.Y. (1993). A stochastic model of radiation carcinogenesis: latent time distributions and their properties. Mathemat. Biosci. 113:51–75.
- Kuk, A. Y.C., Chen, C.H. (1992). A mixture model combining logistic regression with proportional hazards regression. Biometrika 79:531–541.
- Lange, K. (1995). A gradient algorithm locally equivalent to the EM algorithm. J. Roy. Statist. Soc. Ser. B 57:425–437.
- Louis, T.A. (1982). Finding the observed information matrix when using the EM algorithm. J. Roy. Statist. Soc. Ser. B 44:226–233.
- McLachlan, G.J., Krishnan, T. (2008). The EM Algorithm and Extensions. 2nd ed. Hoboken, NJ: John Wiley & Sons.
- Meeker, W.Q., Escobar, L.A. (1998). Statistical Methods for Reliability Data. New York: John Wiley & Sons.
- Rigby, R.A., Stasinopoulos, D.M. (2005). Generalized additive models for location, scale and shape (with discussion). Applied Statistics 54:507–554.
- Rodrigues, J., de Castro, M., Balakrishnan, N., Cancho, V.G. (2011). Destructive weighted Poisson cure rate models. Lifetime Data Anal. 17:333–346.
- Rodrigues, J., Cancho, V.G., de Castro, M., Balakrishnan, N. (2012). A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data. Statist. Meth. Med. Res. 21:585–597.
- Rodrigues, J., de Castro, M., Cancho, V.G., Balakrishnan, N. (2009a). COM-Poisson cure rate survival models and an application to a cutaneous melanoma data. J. Statist. Plann. Infer. 139:3605–3611.
- Rodrigues, J., Cancho, V.G., de Castro, M., Louzada-Neto, F. (2009b). On the unification of the long-term survival models. Statist. Probab. Lett. 79:753–759.
- Self, S.G., Liang, K.-Y. (1987). Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under nonstandard conditions. J. Amer. Statist. Assoc. 82:605–610.
- Shmueli, G., Minka, T.P., Kadane, J.B., Borle, S., Boatwright, P. (2005). A useful distribution for fitting discrete data: revival of the Conway-Maxwell-Poisson distribution. J. Roy. Statist. Soc. Ser. C 54:127–142.
- Stasinopoulos, D.M., Rigby, R.A. (2007). Generalized additive models for location, scale and shape (GAMLSS) in R. J. Statist. Softw. 23:1–46.
- Sy, J.P., Taylor, J. M.G. (2000). Estimation in a Cox proportional hazards cure model. Biometrics 56:227–236.
- Tsodikov, A.D., Ibrahim, J.G., Yakovlev, A.Y. (2003). Estimating cure rates from survival data: an alternative to two-component mixture models. J. Amer. Statist. Assoc. 98:1063–1078.
- Yakovlev, A.Y., Tsodikov, A.D. (1996). Stochastic Models of Tumor Latency and their Biostatistical Applications. Singapore: World Scientific.
- Yakovlev, A.Y., Tsodikov, A.D., Bass, L. (1993). A stochastic-model of hormesis. Mathemat. Biosci. 116:197–219.
- Yin, G., Ibrahim, J.G. (2005). Cure rate models: a unified approach. Can. J. Statist. 33:559–570.