This module produces a table to summarize events by grade.
Usage
tm_t_events_by_grade(
label,
dataname,
parentname = ifelse(inherits(arm_var, "data_extract_spec"),
teal.transform::datanames_input(arm_var), "ADSL"),
arm_var,
hlt,
llt,
grade,
grading_groups = list(`Any Grade (%)` = c("1", "2", "3", "4", "5"), `Grade 1-2 (%)` =
c("1", "2"), `Grade 3-4 (%)` = c("3", "4"), `Grade 5 (%)` = "5"),
col_by_grade = FALSE,
prune_freq = 0,
prune_diff = 0,
add_total = TRUE,
total_label = default_total_label(),
na_level = default_na_str(),
drop_arm_levels = TRUE,
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
.- arm_var
(
teal.transform::choices_selected()
)
object with all available choices and preselected option for variable names that can be used asarm_var
. It defines the grouping variable in the results table.- hlt
(
teal.transform::choices_selected()
)
name of the variable with high level term for events.- llt
(
teal.transform::choices_selected()
)
name of the variable with low level term for events.- grade
(
character
)
name of the severity level variable.- grading_groups
(
list
)
named list of grading groups used whencol_by_grade = TRUE
.- col_by_grade
(
logical
)
whether to display the grading groups in nested columns.- prune_freq
(
number
)
threshold to use for trimming table using event incidence rate in any column.- prune_diff
(
number
)
threshold to use for trimming table using as criteria difference in rates between any two columns.- 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")
.- 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")
.- drop_arm_levels
(
logical
)
whether to drop unused levels ofarm_var
. IfTRUE
,arm_var
levels are set to those used in thedataname
dataset. IfFALSE
,arm_var
levels are set to those used in theparentname
dataset. Ifdataname
andparentname
are the same, thendrop_arm_levels
is set toTRUE
and user input for this parameter is ignored.- 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 Module
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
.lbls_adae <- col_labels(tmc_ex_adae)
ADAE <- tmc_ex_adae %>%
mutate_if(is.character, as.factor) #' be certain of having factors
col_labels(ADAE) <- .lbls_adae
})
join_keys(data) <- default_cdisc_join_keys[names(data)]
ADSL <- data[["ADSL"]]
ADAE <- data[["ADAE"]]
app <- init(
data = data,
modules = modules(
tm_t_events_by_grade(
label = "Adverse Events by Grade Table",
dataname = "ADAE",
arm_var = choices_selected(c("ARM", "ARMCD"), "ARM"),
llt = choices_selected(
choices = variable_choices(ADAE, c("AETERM", "AEDECOD")),
selected = c("AEDECOD")
),
hlt = choices_selected(
choices = variable_choices(ADAE, c("AEBODSYS", "AESOC")),
selected = "AEBODSYS"
),
grade = choices_selected(
choices = variable_choices(ADAE, c("AETOXGR", "AESEV")),
selected = "AETOXGR"
)
)
)
)
#> Initializing tm_t_events_by_grade
#> Initializing reporter_previewer_module
if (interactive()) {
shinyApp(app$ui, app$server)
}