Description Usage Arguments Examples
View source: R/plot_ceteris_paribus.R
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.
1 2 3 4 5 6 7 8 9 |
x |
object of class "surv_ceteris_paribus_explainer" |
... |
arguments to be passed to methods, such as graphical parameters for function |
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 |
1 2 3 4 5 6 7 8 9 10 11 12 13 | library(survxai)
library(rms)
data("pbcTest")
data("pbcTrain")
predict_times <- function(model, data, times){
prob <- rms::survest(model, data, times = times)$surv
return(prob)
}
cph_model <- cph(Surv(years, status)~sex + bili + stage, data=pbcTrain, surv=TRUE, x = TRUE, y=TRUE)
surve_cph <- explain(model = cph_model, data = pbcTest[,-c(1,5)],
y = Surv(pbcTest$years, pbcTest$status), predict_function = predict_times)
cp_cph <- ceteris_paribus(surve_cph, pbcTest[1,-c(1,5)])
plot(cp_cph)
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