Skip to contents

Distribution Module

tm_g_distribution.Rd

Distribution Module

Usage 

tm_g_distribution(
  label = "Distribution Module",
  dist_var,
  strata_var = NULL,
  group_var = NULL,
  freq = FALSE,
  ggtheme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void",
    "test"),
  ggplot2_args = teal.widgets::ggplot2_args(),
  bins = c(30L, 1L, 100L),
  plot_height = c(600, 200, 2000),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL
)

Arguments

label

(character) Label shown in the navigation item for the module.

dist_var

(data_extract_spec or list of multiple data_extract_spec) Variable to consider for the distribution analysis.

strata_var

(data_extract_spec or list of multiple data_extract_spec) Categorical variable to split the selected distribution variable on.

group_var

optional, (data_extract_spec or list of multiple data_extract_spec) Which data columns to use for faceting rows.

freq

optional, (logical) Whether to display frequency (TRUE) or density (FALSE). Defaults to density (FALSE).

ggtheme

optional, (character) ggplot2 theme to be used by default. One of c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void", "test"). Each theme can be chosen by the user during the session. Defaults to "gray".

ggplot2_args

optional, (ggplot2_args) 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", "Histogram", "QQplot").

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

bins

optional, (integer(1) or integer(3)) If scalar then the histogram bins will have a fixed size. If a slider should be presented to adjust the number of histogram bins dynamically then it can be a vector of length three with c(value, min, max). Defaults to c(30L, 1L, 100L).

plot_height

optional, (numeric) A vector of length three with c(value, min and max) for a slider encoding the plot height.

plot_width

optional, (numeric) A vector of length three with c(value, min and max) for a slider encoding the plot width.

pre_output

(shiny.tag, optional)
with text placed before the output to put the output into context. For example a title.

post_output

(shiny.tag, optional) with text placed after the output to put the output into context. For example the shiny::helpText() elements are useful.

Details

Module to analyze and explore univariate variable distribution

Examples 

# Example with non-clinical data
app <- init(
  data = teal_data(dataset("iris", iris)),
  modules = list(
    tm_g_distribution(
      dist_var = data_extract_spec(
        dataname = "iris",
        select = select_spec(variable_choices("iris"), "Petal.Length")
      ),
      ggplot2_args = teal.widgets::ggplot2_args(labs = list(subtitle = "Plot generated by Distribution Module"))
    )
  )
)
#> [INFO] 2022-06-14 17:42:32.1896 pid:1110 token:[] teal.modules.general Initializing tm_g_distribution
if (FALSE) {
shinyApp(app$ui, app$server)
}

# Example with clinical data
library(scda)
ADSL <- synthetic_cdisc_data("latest")$adsl

vars1 <- choices_selected(variable_choices(ADSL, c("ARM", "COUNTRY", "SEX")), selected = NULL)

app <- init(
  data = cdisc_data(
    cdisc_dataset("ADSL", ADSL),
    code = "ADSL <- synthetic_cdisc_data(\"latest\")$adsl",
    check = FALSE
  ),
  modules = modules(
    tm_g_distribution(
      dist_var = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(ADSL, c("AGE", "BMRKR1")),
          selected = "BMRKR1",
          multiple = FALSE,
          fixed = FALSE
        )
      ),
      strata_var = data_extract_spec(
        dataname = "ADSL",
        filter = filter_spec(
          vars = vars1,
          multiple = TRUE
        )
      ),
      group_var = data_extract_spec(
        dataname = "ADSL",
        filter = filter_spec(
          vars = vars1,
          multiple = TRUE
        )
      ),
      ggplot2_args = teal.widgets::ggplot2_args(labs = list(subtitle = "Plot generated by Distribution Module"))
    )
  )
)
#> [INFO] 2022-06-14 17:42:33.2233 pid:1110 token:[] teal.modules.general Initializing tm_g_distribution
if (FALSE) {
shinyApp(app$ui, app$server)
}