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teal Module: Confidence Interval Plot

Source: R/tm_g_ci.R, R/tm_g_ci_picks.R
tm_g_ci.Rd

This module produces a ggplot2::ggplot() type confidence interval plot consistent with the TLG Catalog template CIG01 available here.

Usage 

tm_g_ci(
  label,
  x_var,
  y_var,
  paramcd = NULL,
  avisit = NULL,
  color,
  stat = c("mean", "median"),
  conf_level = teal.picks::values(c(0.95, 0.9, 0.8), 0.95),
  plot_height = c(700L, 200L, 2000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  ggplot2_args = teal.widgets::ggplot2_args(),
  transformators = list(),
  decorators = list()
)

# S3 method for class 'data_extract_spec'
tm_g_ci(
  label,
  x_var,
  y_var,
  paramcd = NULL,
  avisit = NULL,
  color,
  stat = c("mean", "median"),
  conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order =
    TRUE),
  plot_height = c(700L, 200L, 2000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  ggplot2_args = teal.widgets::ggplot2_args(),
  transformators = list(),
  decorators = list()
)

# Default S3 method
tm_g_ci(
  label,
  x_var,
  y_var,
  paramcd,
  avisit,
  color,
  stat = c("mean", "median"),
  conf_level = teal.picks::values(c(0.95, 0.9, 0.8), 0.95),
  plot_height = c(700L, 200L, 2000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  ggplot2_args = teal.widgets::ggplot2_args(),
  transformators = list(),
  decorators = list()
)

Arguments

label

(character)
menu item label of the module in the teal app.

x_var

(teal.picks::variables(), teal.picks::picks(), or legacy data_extract_spec)
treatment-axis encoding.

y_var

(teal.picks::variables(), teal.picks::picks(), or legacy data_extract_spec)
analysis-value encoding.

paramcd

(teal.picks::variables(); legacy teal.transform objects are deprecated but still accepted)
object with all available choices and preselected option for the parameter code variable from dataname.

avisit

(teal.picks::variables(); legacy teal.transform objects are deprecated but still accepted)
value of analysis visit AVISIT of interest.

color

(teal.picks::variables(), teal.picks::picks(), or legacy data_extract_spec)
grouping variable for colors, shapes, and line types.

stat

(character)
statistic to plot. Options are "mean" and "median".

conf_level

(teal.picks::values(); legacy teal.transform::choices_selected() is deprecated but still accepted)
available confidence levels and default selection, each in the range (0, 1).

plot_height

(numeric) optional
vector of length three with c(value, min, max). Specifies the height of the main plot and renders a slider on the plot to interactively adjust the plot height.

plot_width

(numeric) optional
vector of length three with c(value, min, max). Specifies the width of the main plot and renders a slider on the plot to interactively adjust 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.

ggplot2_args

(ggplot2_args) optional
object created by teal.widgets::ggplot2_args() with settings for the module plot. The argument is merged with option teal.ggplot2_args and with default module arguments (hard coded in the module body). For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets").

transformators

(list of teal_transform_module) that will be applied to transform module's data input. To learn more check vignette("transform-input-data", package = "teal").

decorators

[Experimental] (named list of lists of teal_transform_module) optional, decorator for tables or plots included in the module output reported. The decorators are applied to the respective output objects.

See section "Decorating Module" below for more details.

Value

a teal_module object.

Methods (by class)

  • tm_g_ci(data_extract_spec): Legacy encodings via data_extract_spec (merge-based UI).

  • tm_g_ci(default): teal.picks encodings via picks objects for x_var, y_var, and color (use tm_g_ci() to pass teal.picks::variables() objects; they are wrapped into picks).

Decorating Module

This module generates the following objects, which can be modified in place using decorators:

  • plot (ggplot)

A Decorator is applied to the specific output using a named list of teal_transform_module objects. The name of this list corresponds to the name of the output to which the decorator is applied. See code snippet below:

tm_g_ci(
   ..., # arguments for module
   decorators = list(
     plot = teal_transform_module(...) # applied only to `plot` output
   )
)

For additional details and examples of decorators, refer to the vignette vignette("decorate-module-output", package = "teal.modules.clinical").

To learn more please refer to the vignette vignette("transform-module-output", package = "teal") or the teal::teal_transform_module() documentation.

Reporting

This module returns an object of class teal_module, that contains a server function. Since the server function returns a teal_report object, this makes this module reportable, which means that the reporting functionality will be turned on automatically by the teal framework.

For more information on reporting in teal, see the vignettes:

See also

The TLG Catalog where additional example apps implementing this module can be found.

Examples in Shinylive

example-1

Open in Shinylive

Examples 

library(nestcolor)

data <- teal_data()
data <- within(data, {
  library(dplyr)
  ADSL <- tmc_ex_adsl
  ADLB <- tmc_ex_adlb
})
join_keys(data) <- default_cdisc_join_keys[names(data)]

app <- init(
  data = data,
  modules = modules(
    tm_g_ci(
      label = "Confidence Interval Plot",
      x_var = picks(
        datasets("ADSL", "ADSL"),
        variables(c("ARMCD", "BMRKR2"), "ARMCD")
      ),
      y_var = picks(
        datasets("ADLB", "ADLB"),
        variables(c("AVAL", "CHG"), "AVAL")
      ),
      color = picks(
        datasets("ADSL", "ADSL"),
        variables(c("SEX", "STRATA1", "STRATA2"), "STRATA1")
      ),
      paramcd = picks(
        datasets("ADLB", "ADLB"),
        variables("PARAMCD", "PARAMCD"),
        values(selected = "ALT", multiple = FALSE)
      ),
      avisit = picks(
        datasets("ADLB", "ADLB"),
        variables("AVISIT", "AVISIT"),
        values(selected = "SCREENING", multiple = FALSE)
      )
    )
  )
)
#> Initializing tm_g_ci
#> Warning: rlang::dots_list(..., .ignore_empty = "trailing")
#>  - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't guarantee that `selected` is a subset of `choices`.
#> Warning: rlang::dots_list(..., .ignore_empty = "trailing")
#>  - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't guarantee that `selected` is a subset of `choices`.
if (interactive()) {
  shinyApp(app$ui, app$server)
}