teal module: Stack plots of variables and show association with reference variable

Module provides functionality for visualizing the distribution of variables and their association with a reference variable. It supports configuring the appearance of the plots, including themes and whether to show associations.

Usage

tm_g_association(
  label = "Association",
  ref,
  vars,
  show_association = TRUE,
  plot_height = c(600, 400, 5000),
  plot_width = NULL,
  distribution_theme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic",
    "void"),
  association_theme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic",
    "void"),
  pre_output = NULL,
  post_output = NULL,
  ggplot2_args = teal.widgets::ggplot2_args()
)

Arguments

label

(character(1)) Label shown in the navigation item for the module or module group. For modules() defaults to "root". See Details.

ref

(data_extract_spec or list of multiple data_extract_spec) Reference variable, must accepts a data_extract_spec with select_spec(multiple = FALSE) to ensure single selection option.

vars

(data_extract_spec or list of multiple data_extract_spec) Variables to be associated with the reference variable.

show_association

(logical) optional, whether show association of vars with reference variable. Defaults to TRUE.

plot_height

(numeric) optional, specifies the plot height as a three-element vector of value, min, and max intended for use with a slider UI element.

plot_width

(numeric) optional, specifies the plot width as a three-element vector of value, min, and max for a slider encoding the plot width.

distribution_theme, association_theme

(character) optional, ggplot2 themes to be used by default. Default to "gray".

pre_output

(shiny.tag) optional, text or UI element to be displayed before the module's output, providing context or a title. with text placed before the output to put the output into context. For example a title.

post_output

(shiny.tag) optional, text or UI element to be displayed after the module's output, adding context or further instructions. Elements like shiny::helpText() are useful.

ggplot2_args

(ggplot2_args) optional, object created by teal.widgets::ggplot2_args() with settings for all the plots or named list of ggplot2_args objects for plot-specific settings. The argument is merged with options variable teal.ggplot2_args and default module setup.

List names should match the following: c("default", "Bivariate1", "Bivariate2").

For more details see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets").

Value

Object of class teal_module to be used in teal applications.

Note

For more examples, please see the vignette "Using association plot" via vignette("using-association-plot", package = "teal.modules.general").

Examples

library(teal.widgets)

# general data example
data <- teal_data()
data <- within(data, {
  require(nestcolor)
  CO2 <- CO2
  factors <- names(Filter(isTRUE, vapply(CO2, is.factor, logical(1L))))
  CO2[factors] <- lapply(CO2[factors], as.character)
})
datanames(data) <- c("CO2")

app <- init(
  data = data,
  modules = modules(
    tm_g_association(
      ref = data_extract_spec(
        dataname = "CO2",
        select = select_spec(
          label = "Select variable:",
          choices = variable_choices(data[["CO2"]], c("Plant", "Type", "Treatment")),
          selected = "Plant",
          fixed = FALSE
        )
      ),
      vars = data_extract_spec(
        dataname = "CO2",
        select = select_spec(
          label = "Select variables:",
          choices = variable_choices(data[["CO2"]], c("Plant", "Type", "Treatment")),
          selected = "Treatment",
          multiple = TRUE,
          fixed = FALSE
        )
      ),
      ggplot2_args = ggplot2_args(
        labs = list(subtitle = "Plot generated by Association Module")
      )
    )
  )
)
#> [INFO] 2024-03-01 20:55:27.3611 pid:1280 token:[] teal.modules.general Initializing tm_g_association
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# CDISC data example
data <- teal_data()
data <- within(data, {
  require(nestcolor)
  ADSL <- rADSL
})
datanames(data) <- "ADSL"
join_keys(data) <- default_cdisc_join_keys[datanames(data)]

app <- init(
  data = data,
  modules = modules(
    tm_g_association(
      ref = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Select variable:",
          choices = variable_choices(
            data[["ADSL"]],
            c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
          ),
          selected = "RACE",
          fixed = FALSE
        )
      ),
      vars = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Select variables:",
          choices = variable_choices(
            data[["ADSL"]],
            c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
          ),
          selected = "BMRKR2",
          multiple = TRUE,
          fixed = FALSE
        )
      ),
      ggplot2_args = ggplot2_args(
        labs = list(subtitle = "Plot generated by Association Module")
      )
    )
  )
)
#> [INFO] 2024-03-01 20:55:27.4516 pid:1280 token:[] teal.modules.general Initializing tm_g_association
if (interactive()) {
  shinyApp(app$ui, app$server)
}