Run filtering panel locally

Usage

gui(
  cohort,
  steps = TRUE,
  stats = c("pre", "post"),
  run_button = FALSE,
  feedback = TRUE,
  state = TRUE,
  bootstrap = 3,
  enable_bookmarking = TRUE,
  code = TRUE,
  attrition = TRUE,
  show_help = TRUE,
  new_step = c("clone", "configure")
)

Arguments

cohort: Cohort object with configured filters.
steps: Set to TRUE (default) if multiple steps should be available.
stats: Choose which statistics should be displayed for data (and some filters). Possible options are: "pre" - previous step stat, "post" - current step stats, `c("pre", "post")` - for both and NULL for no stats.
run_button: Should Run button be displayed? If so, the current step computations are run only when clicked.
feedback: Set to TRUE (default) if feedback plots should be displayed at each filter.
state: Set to TRUE (default) to enable get/set state panel.
bootstrap: Boostrap version to be used for filtering panel. See bs_theme version argument.
enable_bookmarking: Set to TRUE (default) if panel should be compatible with native shiny bookmarking.
code: Set to TRUE (default) to enable reproducible code panel.
attrition: Set to TRUE (default) to enable attrition plot panel.
show_help: Set to TRUE (default) to enable help buttons.
new_step: Choose which add step method should be used for creating new step. Possible options are: "clone" - copy filters from last step, "configure" - opening modal and allow to chose filters from available filters.

Value

No return value, used for side effect which is running a Shiny application.

Examples

if (interactive()) {
  library(magrittr)
  library(cohortBuilder)
  library(shinyCohortBuilder)
  mtcars_source <- set_source(tblist(mtcars = mtcars))
  mtcars_cohort <- cohort(
    mtcars_source,
    filter("discrete", id = "am", dataset = "mtcars", variable = "am", value = 1)
  ) %>% run()
  gui(mtcars_cohort)
}