In ShixiangWang/ezcox: Easily Process a Batch of Cox Models

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(survival)
library(ezcox)

forester

For simple and general forest data, you can use forester(), it is lightweight and can be applied to any proper data (not limited to Cox model).

t1 <- ezcox(lung, covariates = c(
  "age", "sex",
  "ph.karno", "pat.karno"
))
p <- forester(t1, xlim = c(0, 1.5))
p
p2 <- forester(t1, xlim = c(0.5, 1.5))
p2

show_forest

For more powerful plot features, you need to use show_forest(). Unlike the forester(), the ezcox() is included in the function.

show_forest(lung, covariates = c("sex", "ph.ecog"), controls = "age")
show_forest(lung, covariates = c("sex", "ph.ecog"), controls = "age", merge_models = TRUE)
show_forest(lung,
  covariates = c("sex", "ph.ecog"), controls = "age", merge_models = TRUE,
  drop_controls = TRUE
)
show_forest(lung,
  covariates = c("sex", "ph.ecog"), controls = "age", merge_models = TRUE,
  vars_to_show = "sex"
)