coef.mixturecure {hdcuremodels}

Extract model coefficients from a fitted mixture cure object

Description

coef.mixturecure is a generic function which extracts the model coefficients from a fitted mixture cure model object fit using curegmifs, cureem, cv_curegmifs, or cv_cureem.

Usage

## S3 method for class 'mixturecure'
coef(object, model.select = "AIC", ...)

Arguments

object

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

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.

...

other arguments.

Value

a list of estimated parameters extracted from the model object using the model selection criterion

See Also

curegmifs, cureem, summary.mixturecure, plot.mixturecure, predict.mixturecure

Examples

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