calculates the predicted cure indicators from a mixture cure model with the survival of uncured specified by a Weibull distribution.
predcall_wei(
object,
pred,
z_pcured = z_pcured,
z_ucured = z_ucured,
x = x,
level = level,
epsilon = epsilon,
sign_delta = 1,
cumLexctopred
)ouput from a model implemented using curesurv
some predicted estimates
covariates matrix acting on cure proportion
covariates matrix acting on survival function of uncured
time at which the predictions are provided
(1-alpha/2)-order quantile of a normal distribution
value fixed by user to estimate the TTC \(\text{Pi}(t)\geq (1-\epsilon)\). By default \(\epsilon = 0.05\).
only used for mixture cure rate models to specify if the effects or minus the effects of covariates acting on uncured survival to be considered. Default will be sign_delta = "1". The alternative is sign_delta = "-1".
pre prediction obtained by cumLexc_alphaweibull_topred
Juste Goungounga, Judith Breaud, Olayide Boussari, Laura Botta, Valerie Jooste
Boussari O, Bordes L, Romain G, Colonna M, Bossard N, Remontet L, Jooste V. Modeling excess hazard with time-to-cure as a parameter. Biometrics. 2021 Dec;77(4):1289-1302. doi: 10.1111/biom.13361. Epub 2020 Sep 12. PMID: 32869288. (pubmed)
Boussari O, Romain G, Remontet L, Bossard N, Mounier M, Bouvier AM, Binquet C, Colonna M, Jooste V. A new approach to estimate time-to-cure from cancer registries data. Cancer Epidemiol. 2018 Apr;53:72-80. doi: 10.1016/j.canep.2018.01.013. Epub 2018 Feb 4. PMID: 29414635. (pubmed)
Phillips N, Coldman A, McBride ML. Estimating cancer prevalence using mixture models for cancer survival. Stat Med. 2002 May 15;21(9):1257-70. doi: 10.1002/sim.1101. PMID: 12111877. (pubmed)
De Angelis R, Capocaccia R, Hakulinen T, Soderman B, Verdecchia A. Mixture models for cancer survival analysis: application to population-based data with covariates. Stat Med. 1999 Feb 28;18(4):441-54. doi: 10.1002/(sici)1097-0258(19990228)18:4<441::aid-sim23>3.0.co;2-m. PMID: 10070685. (pubmed)