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teal module: Distribution analysis

Source: R/tm_g_distribution.R
tm_g_distribution.Rd

Module is designed to explore the distribution of a single variable within a given dataset. It offers several tools, such as histograms, Q-Q plots, and various statistical tests to visually and statistically analyze the variable's distribution.

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

dist_var

(data_extract_spec or list of multiple data_extract_spec) Variable(s) for which the distribution will be analyzed.

strata_var

(data_extract_spec or list of multiple data_extract_spec) Categorical variable used to split the distribution analysis.

group_var

(data_extract_spec or list of multiple data_extract_spec) Variable used for faceting plot into multiple panels.

freq

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

ggtheme

(character) optional, ggplot2 theme to be used by default. Defaults to "gray".

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", "Histogram", "QQplot").

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

bins

(integer(1) or integer(3)) optional, specifies the number of bins for the histogram.

  • When the length of bins is one: The histogram bins will have a fixed size based on the bins provided.

  • When the length of bins is three: The histogram bins are dynamically adjusted based on vector of value, min, and max. Defaults to c(30L, 1L, 100L).

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.

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.

Value

Object of class teal_module to be used in teal applications.

Examples 

library(teal.widgets)

# general data example
data <- teal_data()
data <- within(data, {
  iris <- iris
})
datanames(data) <- "iris"

app <- init(
  data = data,
  modules = list(
    tm_g_distribution(
      dist_var = data_extract_spec(
        dataname = "iris",
        select = select_spec(variable_choices("iris"), "Petal.Length")
      ),
      ggplot2_args = ggplot2_args(
        labs = list(subtitle = "Plot generated by Distribution Module")
      )
    )
  )
)
#> [INFO] 2024-03-01 20:55:28.7184 pid:1280 token:[] teal.modules.general Initializing tm_g_distribution
#> Registered S3 methods overwritten by 'ggpp':
#>   method                  from   
#>   heightDetails.titleGrob ggplot2
#>   widthDetails.titleGrob  ggplot2
#> Registered S3 method overwritten by 'ggpmisc':
#>   method                  from   
#>   as.character.polynomial polynom
if (interactive()) {
  shinyApp(app$ui, app$server)
}

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

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

app <- init(
  data = data,
  modules = modules(
    tm_g_distribution(
      dist_var = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(data[["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 = ggplot2_args(
        labs = list(subtitle = "Plot generated by Distribution Module")
      )
    )
  )
)
#> [INFO] 2024-03-01 20:55:28.9948 pid:1280 token:[] teal.modules.general Initializing tm_g_distribution
if (interactive()) {
  shinyApp(app$ui, app$server)
}