Show Forest Plot — show_forest • ezcox

This is a wrapper of function ezcox, get_models and show_models. It focus on generating forest plot easily and flexibly.

show_forest(
  data,
  covariates,
  controls = NULL,
  time = "time",
  status = "status",
  merge_models = FALSE,
  model_names = NULL,
  vars_to_show = NULL,
  drop_controls = FALSE,
  add_caption = TRUE,
  point_size = 3,
  point_shape = 15,
  color = "red",
  banded = TRUE,
  headings = list(variable = "Variable", n = "N", measure = "Hazard ratio", ci = NULL,
    p = "p"),
  model_dir = file.path(tempdir(), "ezcox"),
  verbose = TRUE,
  ...
)

Arguments

data: a data.frame containing variables, time and os status.
covariates: a character vector optionally listing the variables to include in the plot (defaults to all variables).
controls: column names specifying controls. The names with pattern "*:|()" will be treated as interaction/combination term, please make sure all column names in data are valid R variable names.
time: column name specifying time, default is 'time'.
status: column name specifying event status, default is 'status'.
merge_models: if 'TRUE', merge all models and keep the plot tight.
model_names: model names to show when merge_models=TRUE.
vars_to_show: default is NULL, show all variables (including controls). You can use this to choose variables to show, but remember, the models have not been changed.
drop_controls: works when covariates=NULL and models is a ezcox_models, if TRUE, it removes control variables automatically.
add_caption: if TRUE, add caption to the plot.
point_size: size of point.
point_shape: shape value of point.
color: color for point and segment.
banded: if TRUE (default), create banded background color.
headings: a list for setting the heading text.
model_dir: a path for storing model results.
verbose: if TRUE, print extra info.
...: other arguments passing to forestmodel::forest_model().

Value

a ggplot object

Examples

library(survival)
show_forest(lung, covariates = c("sex", "ph.ecog"), controls = "age")
#> => Processing variable sex
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.
#> => Processing variable ph.ecog
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.

show_forest(lung, covariates = c("sex", "ph.ecog"), controls = "age", merge_models = TRUE)
#> => Processing variable sex
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.
#> => Processing variable ph.ecog
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.

show_forest(lung,
  covariates = c("sex", "ph.ecog"), controls = "age", merge_models = TRUE,
  drop_controls = TRUE
)
#> => Processing variable sex
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.
#> => Processing variable ph.ecog
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.
#> covariates=NULL but drop_controls=TRUE, detecting controls...
#> Yes. Setting variables to keep...
#> Done.

p <- show_forest(lung,
  covariates = c("sex", "ph.ecog"), controls = "age", merge_models = TRUE,
  vars_to_show = "sex"
)
#> => Processing variable sex
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.
#> => Processing variable ph.ecog
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.
#> Resized limits to included dashed line in forest panel
p