coef.mixturecure
is a generic function which extracts the model
coefficients from a fitted mixturecure
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 fromcuregmifs
,cureem
,cv_curegmifs
, orcv_cureem
.- model_select
either a case-sensitive parameter for models fit using
curegmifs
orcureem
or any numeric step along the solution path can be selected. The default ismodel_select = "AIC"
which calculates the predicted values using the coefficients from the model achieving the minimum AIC. The complete list of options are:"AIC"
for the minimum AIC (default)."mAIC"
for the minimum modified AIC."cAIC"
for the minimum corrected AIC."BIC"
, for the minimum BIC."mBIC"
for the minimum modified BIC."EBIC"
for the minimum extended BIC."logLik"
for the step that maximizes the log-likelihood.n
where n is any numeric value from the solution path.
This option has no effect for objects fit using
cv_curegmifs
orcv_cureem
.- ...
other arguments.
Value
- rate
estimated rate parameter when fitting a Weibull or exponential mixture cure model.
- shape
estimated shape parameter when fitting a Weibull mixture cure model.
- b0
estimated intercept for the incidence portion of the mixture cure model.
- beta_inc
the vector of coefficient estimates for the incidence portion of the mixture cure model.
- beta_lat
the vector of coefficient estimates for the latency portion of the mixture cure model.
- p_uncured
a vector of probabilities from the incidence portion of the fitted model representing the P(uncured).
Examples
library(survival)
withr::local_seed(1234)
temp <- generate_cure_data(n = 100, j = 10, n_true = 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)
#> $rate
#> [1] 3.584565
#>
#> $shape
#> [1] 1.197495
#>
#> $b0
#> [1] 0.3670091
#>
#> $beta_inc
#> U1 U2 X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
#> 0.00 0.07 1.46 -1.23 1.22 -1.33 0.04 -1.37 -0.90 0.36 -0.07 1.77
#>
#> $beta_lat
#> U1 U2 X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
#> 0.37 0.34 1.24 1.07 0.39 1.11 -0.84 0.04 0.71 0.38 -0.45 -1.20
#>