concordance_mcm {hdcuremodels}

C-statistic for mixture cure models

Description

This function calculates the C-statistic using the cure status weighting (CSW) method proposed by Asano and Hirakawa.

Usage

concordance_mcm(object, newdata, cure_cutoff = 5, model.select = "AIC")

Arguments

object

a mixturecure object resulting from curegmifs, cureem, cv_curegmifs, cv_cureem.

newdata

an optional data.frame that minimally includes the incidence and/or latency variables to use for predicting the response. If omitted, the training data are used.

cure_cutoff

cutoff value for cure, used to produce a proxy for the unobserved cure status; default is 5.

model.select

for models fit using curegmifs or cureem any step along the solution path can be selected. The default is model.select = "AIC" which calculates the predicted values using the coefficients from the model having the lowest AIC. Other options are model.select = "mAIC" for the modified AIC, model.select = "cAIC" for the corrected AIC, model.select = "BIC", model.select = "mBIC" for the modified BIC, model.select = "EBIC" for the extended BIC, model.select = "logLik" for the step that maximizes the log-likelihood, or any numeric value from the solution path. This option has no effect for objects fit using cv_curegmifs or cv_cureem.

Value

value of C-statistic for the cure models.

References

Asano, J. and Hirakawa, H. (2017) Assessing the prediction accuracy of a cure model for censored survival data with long-term survivors: Application to breast cancer data. Journal of Biopharmaceutical Statistics, 27:6, 918–932.

See Also

AUC

Examples

library(survival)
set.seed(1234)
temp <- generate_cure_data(N = 100, J = 10, nTrue = 10, A = 1.8)
training <- temp$Training
testing <- temp$Testing
fit <- curegmifs(Surv(Time, Censor) ~ .,
                  data = training, x.latency = training,
                  model = "weibull", thresh = 1e-4, maxit = 2000,
                  epsilon = 0.01, verbose = FALSE)
concordance_mcm(fit)
concordance_mcm(fit, newdata = testing)