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()
)
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(s) in the results table. If there are two elements selected forarm_var
, second variable will be nested under the first variable.- 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")
.
See also
The TLG Catalog where additional example apps implementing this module can be found.
Examples
data <- teal_data()
data <- within(data, {
library(dplyr)
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
})
datanames <- c("ADSL", "ADAE")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]
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(data[["ADAE"]], c("AETERM", "AEDECOD")),
selected = c("AEDECOD")
),
hlt = choices_selected(
choices = variable_choices(data[["ADAE"]], c("AEBODSYS", "AESOC")),
selected = "AEBODSYS"
),
grade = choices_selected(
choices = variable_choices(data[["ADAE"]], c("AETOXGR", "AESEV")),
selected = "AETOXGR"
)
)
)
)
#> Initializing tm_t_events_by_grade
if (interactive()) {
shinyApp(app$ui, app$server)
}