## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", warning = FALSE, message = FALSE ) ## ----setup-------------------------------------------------------------------- library(recforest) library(dplyr) ## ----------------------------------------------------------------------------- data("bladder1_recforest") id_individuals_bladder1_recforest <- unique(bladder1_recforest$id) train_ids <- sample(id_individuals_bladder1_recforest, size = 100, replace = FALSE) test_ids <- setdiff(id_individuals_bladder1_recforest, train_ids) train_bladder1_recforest <- bladder1_recforest %>% filter(id %in% train_ids) test_bladder1_recforest <- bladder1_recforest %>% filter(id %in% test_ids) ## ----------------------------------------------------------------------------- set.seed(1234) trained_forest <- train_forest( data = train_bladder1_recforest, id_var = "id", covariates = c("treatment", "number", "size"), time_vars = c("t.start", "t.stop"), death_var = "death", event = "event", n_trees = 3, n_bootstrap = round(2 * length(train_ids) / 3), mtry = 2, minsplit = 3, nodesize = 15, method = "NAa", min_score = 5, max_nodes = 20, seed = 111, parallel = FALSE, verbose = FALSE ) ## ----------------------------------------------------------------------------- predictions <- predict( trained_forest, newdata = test_bladder1_recforest, id_var = "id", covariates = c("treatment", "number", "size"), time_vars = c("t.start", "t.stop"), death_var = "death" )