Function plot for ceteris_paribus object visualise estimated survival curve of mean probabilities in chosen time points. Black lines on each plot correspond to survival curve for our new observation specified in the ceteris_paribus function.

# S3 method for surv_ceteris_paribus_explainer
plot(x, ...,
selected_variable = NULL, scale_type = "factor", scale_col = NULL,
ncol = 1)

## Arguments

x object of class "surv_ceteris_paribus_explainer" other arguments name of variable we want to draw ceteris paribus plot type of scale of colors, either "discrete" or "gradient" vector containing values of low and high ends of the gradient, when "gradient" type of scale was chosen number of columns for faceting

## Examples

library(survxai)
library(rms)
data("pbcTest")
data("pbcTrain")
predict_times <- function(model, data, times){
prob <- rms::survest(model, data, times = times)$surv return(prob) } cph_model <- cph(Surv(years, status)~., data=pbcTrain, surv=TRUE, x = TRUE, y=TRUE) surve_cph <- explain(model = cph_model, data = pbcTest[,-c(1,5)], y = Surv(pbcTest$years, pbcTest\$status), predict_function = predict_times)
cp_cph <- ceteris_paribus(surve_cph, pbcTest[1,-c(1,5)])
plot(cp_cph)