v0.2.5

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: bmstate
 Type: Package
 Title: Bayesian multistate modeling
-Version: 0.2.4
+Version: 0.2.5
 Authors@R:
     c(person(given = "Juho",
            family = "Timonen",

NAMESPACE

@@ -9,6 +9,7 @@ export(PKModel)
 export(PSSDosingData)
 export(PathData)
 export(TransitionMatrix)
+export(as_any_event)
 export(as_single_event)
 export(as_survival)
 export(c_index)

R/PathData.R

@@ -527,6 +527,26 @@ potential_covariates <- function(pd, possible = NULL, ...) {
   df
 }
 
+#' PathData to time-to-event data format for any state other than null state
+#'
+#' @export
+#' @inheritParams as_single_event
+#' @return A \code{\link{PathData}} object
+as_any_event <- function(pd, null_state = "Randomization") {
+  pd_new <- pd$clone(deep = TRUE)
+  df <- pd_new$path_df
+  idx <- which(pd_new$transmat$states == null_state)
+  if (length(idx) != 1) {
+    stop("error")
+  }
+  df$state[which(df$state == idx)] <- 1
+  df$state[which(df$state != 1)] <- 2
+  tm <- transmat_survival(state_names = c(null_state, "Any event"))
+  pd_new$path_df <- df
+  pd_new$transmat <- tm
+  as_single_event(pd_new, "Any event", null_state)
+}
+
 #' PathData to time-to-event data format with a single event
 #'
 #' @export

R/stan.R

@@ -138,7 +138,8 @@ fit_stan <- function(model, data,
   info <- list(
     diag = diag,
     runset = stan_fit$runset,
-    summary = smr$result
+    summary = smr$result,
+    time = stan_fit$time()
   )
   fit <- MultistateModelFit$new(data, sd, model, draws, info)
   if (!return_stanfit) {

tests/testthat/test-cav.R

@@ -1,7 +1,7 @@
-library(ggplot2)
-library(dplyr)
-
 test_that("cav data analysis works", {
+  library(ggplot2)
+  library(dplyr)
+
   # Modify original data like in
   # https://rviews.rstudio.com/2023/04/19/multistate-models-for-medical-applications/
   df_full <- as_tibble(msm::cav) |>

tests/testthat/test-workflow.R

@@ -40,6 +40,10 @@ test_that("entire workflow works", {
   fit <- a$fit
   expect_true(inherits(fit, "MultistateModelFit"))
 
+  # Test
+  a <- as_any_event(jd$train$paths, "Healthy")
+  checkmate::assert_true(all(a$state_names() == c("Healthy", "Any event")))
+
   # Print
   expect_output(print(fit), "A MultistateModelFit with 30 draws")