Show Cox Models

show_models(
  models,
  model_names = NULL,
  covariates = NULL,
  merge_models = FALSE,
  drop_controls = FALSE,
  headings = list(variable = "Variable", n = "N", measure = "Hazard ratio", ci = NULL,
    p = "p"),
  ...
)

Arguments

models: a ezcox_models from get_models() or a (named) list of Cox models.
model_names: model names to show when merge_models=TRUE.
covariates: a character vector optionally listing the variables to include in the plot (defaults to all variables).
merge_models: if 'TRUE', merge all models and keep the plot tight.
drop_controls: works when covariates=NULL and models is a ezcox_models, if TRUE, it removes control variables automatically.
headings: a list for setting the heading text.
...: other arguments passing to forestmodel::forest_model().

Value

a ggplot object

Examples

library(survival)
zz <- ezcox(lung, covariates = c("sex", "ph.ecog"), controls = "age", return_models = TRUE)
#> => Processing variable sex
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.
#> => Processing variable ph.ecog
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.
mds <- get_models(zz)
show_models(mds)

show_models(mds, model_names = paste0("Model ", 1:2))

show_models(mds, covariates = c("sex", "ph.ecog"))

show_models(mds, drop_controls = TRUE)
#> covariates=NULL but drop_controls=TRUE, detecting controls...
#> Yes. Setting variables to keep...
#> Done.

show_models(mds, merge_models = TRUE)

p <- show_models(mds, merge_models = TRUE, drop_controls = TRUE)
#> covariates=NULL but drop_controls=TRUE, detecting controls...
#> Yes. Setting variables to keep...
#> Done.
p