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

selected_variable

name of variable we want to draw ceteris paribus plot

scale_type

type of scale of colors, either "discrete" or "gradient"

scale_col

vector containing values of low and high ends of the gradient, when "gradient" type of scale was chosen

ncol

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)