Print the contents of a mixture cure fitted object

This function prints the first several incidence and latency coefficients, the rate (when fitting an exponential or Weibull mixture cure model), and alpha (when fitting a Weibull mixture cure model). This function returns the fitted object invisible to the user.

Usage

# S3 method for class 'mixturecure'
print(x, max = 6, ...)

Arguments

x

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

max

maximum number of rows in a matrix or elements in a vector to display

...

other arguments.

Value

prints coefficient estimates for the incidence portion of the model and if included, prints the coefficient estimates for the latency portion of the model. Also prints rate for exponential and Weibull models and scale (alpha) for the Weibull mixture cure model. Returns all objects fit using cureem, curegmifs, cv_cureem, or cv_curegmifs.

Note

The contents of a mixturecure fitted object differ depending upon whether the EM (cureem) or GMIFS (curegmifs) algorithm is used for model fitting or if cross-validation is used. Also, the output differs depending upon whether x_latency is specified in the model (i.e., variables are included in the latency portion of the model fit) or only terms on the right hand side of the equation are included (i.e., variables are included in the incidence portion of the model).

See also

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

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
)
print(fit)
#> mixturecure object fit using Weibull GMIFS algorithm
#> 
#> $b_path
#>      U1 U2   X1 X2 X3 X4
#> [1,]  0  0 0.01  0  0  0
#> [2,]  0  0 0.02  0  0  0
#> [3,]  0  0 0.03  0  0  0
#> [4,]  0  0 0.04  0  0  0
#> [5,]  0  0 0.05  0  0  0
#> [6,]  0  0 0.06  0  0  0
#> 1274 more rows
#> 6 more columns
#> 
#> $beta_path
#>      U1 U2   X1 X2 X3   X4
#> [1,]  0  0 0.01  0  0 0.00
#> [2,]  0  0 0.02  0  0 0.00
#> [3,]  0  0 0.03  0  0 0.00
#> [4,]  0  0 0.03  0  0 0.01
#> [5,]  0  0 0.03  0  0 0.02
#> [6,]  0  0 0.03  0  0 0.03
#> 1274 more rows
#> 6 more columns
#> 
#> $rate
#>  1.74771 1.747557 1.745463 1.776432 1.806308 1.835547 
#> 1274 more elements
#> 
#> $alpha
#>  0.5120896 0.5130922 0.5131297 0.5149383 0.5167088 0.51841 
#> 1274 more elements
#>