Skip to content

Make .check_censor_model() error for non-censored-regression models #972

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Jun 8, 2023
Merged

Make .check_censor_model() error for non-censored-regression models #972

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion DESCRIPTION
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
Package: parsnip
Title: A Common API to Modeling and Analysis Functions
Version: 1.1.0.9002
Version: 1.1.0.9003
Authors@R: c(
person("Max", "Kuhn", , "max@posit.co", role = c("aut", "cre")),
person("Davis", "Vaughan", , "davis@posit.co", role = "aut"),
Expand Down
8 changes: 8 additions & 0 deletions R/survival-censoring-weights.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -63,6 +63,11 @@ trunc_probs <- function(probs, trunc = 0.01) {
}

.check_censor_model <- function(x) {
if (x$spec$mode != "censored regression") {
cli::cli_abort(
"The model needs to be for mode 'censored regression', not for mode '{x$spec$mode}'."
)
}
nms <- names(x)
if (!any(nms == "censor_probs")) {
rlang::abort("Please refit the model with parsnip version 1.0.4 or greater.")
Expand Down Expand Up @@ -245,14 +250,17 @@ add_graf_weights_vec <- function(object, .pred, surv_obj, trunc = 0.05, eps = 10
num_times <- vctrs::list_sizes(.pred)
y <- vctrs::list_unchop(.pred)
y$surv_obj <- vctrs::vec_rep_each(surv_obj, times = num_times)

names(y)[names(y) == ".time"] <- ".eval_time" # Temporary

# Compute the actual time of evaluation
y$.weight_time <- graf_weight_time_vec(y$surv_obj, y$.eval_time, eps = eps)
# Compute the corresponding probability of being censored
y$.pred_censored <- predict(object$censor_probs, time = y$.weight_time, as_vector = TRUE)
y$.pred_censored <- trunc_probs(y$.pred_censored, trunc = trunc)
# Invert the probabilities to create weights
y$.weight_censored = 1 / y$.pred_censored

# Convert back the list column format
y$surv_obj <- NULL
vctrs::vec_chop(y, sizes = num_times)
Expand Down