The module produces an exposure table for risk management plan.
Usage
tm_t_exposure(
label,
dataname,
parentname = ifelse(inherits(col_by_var, "data_extract_spec"),
teal.transform::datanames_input(col_by_var), "ADSL"),
row_by_var,
col_by_var,
paramcd = teal.transform::choices_selected(choices =
teal.transform::value_choices(dataname, "PARAMCD", "PARAM"), selected = "TDURD"),
paramcd_label = "PARAM",
id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
subset = "USUBJID"), selected = "USUBJID", fixed = TRUE),
parcat,
aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
subset = "AVAL"), selected = "AVAL", fixed = TRUE),
avalu_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
subset = "AVALU"), selected = "AVALU", fixed = TRUE),
add_total,
total_label = default_total_label(),
add_total_row = TRUE,
total_row_label = "Total number of patients and patient time*",
na_level = default_na_str(),
pre_output = NULL,
post_output = NULL,
basic_table_args = teal.widgets::basic_table_args(),
decorators = NULL
)
Arguments
- label
(
character
)
menu item label of the module in the teal app.- dataname
(
character
)
analysis data used in teal module.- parentname
(
character
)
parent analysis data used in teal module, usually this refers toADSL
.- row_by_var
(
teal.transform::choices_selected()
)
object with all available choices and preselected option for variable names that can be used to split rows.- col_by_var
(
teal.transform::choices_selected()
)
object with all available choices and preselected option for variable names that can be used to split columns.- paramcd
(
teal.transform::choices_selected()
)
object with all available choices and preselected option for the parameter code variable fromdataname
.- paramcd_label
(
character
)
the column from the dataset where the value will be used to label the argumentparamcd
.- id_var
(
teal.transform::choices_selected()
)
object specifying the variable name for subject id.- parcat
(
teal.transform::choices_selected()
)
object with all available choices and preselected option for parameter category values.- aval_var
(
teal.transform::choices_selected()
)
object with all available choices and pre-selected option for the analysis variable.- avalu_var
(
teal.transform::choices_selected()
)
object with all available choices and preselected option for the analysis unit variable.- add_total
(
logical
)
whether to include column with total number of patients.- total_label
(
string
)
string to display as total column/row label if column/row is enabled (seeadd_total
). Defaults to"All Patients"
. To set a new defaulttotal_label
to apply in all modules, runset_default_total_label("new_default")
.- add_total_row
(
flag
)
whether a "total" level should be added after the others which includes all the levels that constitute the split. A custom label can be set for this level via thetotal_row_label
argument.- total_row_label
(
character
)
string to display as total row label if row is enabled (seeadd_total_row
).- na_level
(
string
)
used to replace allNA
or empty values in character or factor variables in the data. Defaults to"<Missing>"
. To set a defaultna_level
to apply in all modules, runset_default_na_str("new_default")
.- 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 theshiny::helpText()
elements are useful.- basic_table_args
(
basic_table_args
) optional
object created byteal.widgets::basic_table_args()
with settings for the module table. The argument is merged with optionteal.basic_table_args
and with default module arguments (hard coded in the module body). For more details, see the vignette:vignette("custom-basic-table-arguments", package = "teal.widgets")
.- decorators
-
" (
list
ofteal_transform_module
, namedlist
ofteal_transform_module
or"NULL
) optional, if notNULL
, decorator for tables or plots included in the module. When a named list ofteal_transform_module
, the decorators are applied to the respective output objects.Otherwise, the decorators are applied to all objects, which is equivalent as using the name
default
.See section "Decorating Module" below for more details.
Decorating Modules
This module generates the following objects, which can be modified in place using decorators:
table
(TableTree
as created fromrtables::build_table
)
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal")
or the teal_transform_module()
documentation.
See also
The TLG Catalog where additional example apps implementing this module can be found.
Examples
library(dplyr)
data <- teal_data()
data <- within(data, {
ADSL <- tmc_ex_adsl
ADEX <- tmc_ex_adex
set.seed(1, kind = "Mersenne-Twister")
.labels <- col_labels(ADEX, fill = FALSE)
ADEX <- ADEX %>%
distinct(USUBJID, .keep_all = TRUE) %>%
mutate(
PARAMCD = "TDURD",
PARAM = "Overall duration (days)",
AVAL = sample(x = seq(1, 200), size = n(), replace = TRUE),
AVALU = "Days"
) %>%
bind_rows(ADEX)
col_labels(ADEX) <- .labels
})
join_keys(data) <- default_cdisc_join_keys[names(data)]
app <- init(
data = data,
modules = modules(
tm_t_exposure(
label = "Duration of Exposure Table",
dataname = "ADEX",
paramcd = choices_selected(
choices = value_choices(data[["ADEX"]], "PARAMCD", "PARAM"),
selected = "TDURD"
),
col_by_var = choices_selected(
choices = variable_choices(data[["ADEX"]], subset = c("SEX", "ARM")),
selected = "SEX"
),
row_by_var = choices_selected(
choices = variable_choices(data[["ADEX"]], subset = c("RACE", "REGION1", "STRATA1", "SEX")),
selected = "RACE"
),
parcat = choices_selected(
choices = value_choices(data[["ADEX"]], "PARCAT2"),
selected = "Drug A"
),
add_total = FALSE
)
),
filter = teal_slices(teal_slice("ADSL", "SAFFL", selected = "Y"))
)
#> Initializing tm_t_exposure
#> Initializing reporter_previewer_module
if (interactive()) {
shinyApp(app$ui, app$server)
}