This module produces a table to summarize variables.
Usage
tm_t_summary(
label,
dataname,
parentname = ifelse(inherits(arm_var, "data_extract_spec"),
teal.transform::datanames_input(arm_var), "ADSL"),
arm_var,
summarize_vars,
add_total = TRUE,
total_label = default_total_label(),
show_arm_var_labels = TRUE,
useNA = c("ifany", "no"),
na_level = default_na_str(),
numeric_stats = c("n", "mean_sd", "mean_ci", "median", "median_ci", "quantiles",
"range", "geom_mean"),
denominator = c("N", "n", "omit"),
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.- summarize_vars
(
teal.transform::choices_selected()
)
names of the variables that should be summarized.- 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")
.- show_arm_var_labels
(
flag
)
whether arm variable label(s) should be displayed. Defaults toTRUE
.- useNA
(
character
)
whether missing data (NA
) should be displayed as a level.- 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")
.- numeric_stats
(
character
)
names of statistics to display for numeric summary variables. Available statistics aren
,mean_sd
,mean_ci
,median
,median_ci
,quantiles
,range
, andgeom_mean
.- denominator
(
character
)
chooses how percentages are calculated. With optionN
, the reference population from the column total is used as the denominator. With optionn
, the number of non-missing records in this row and column intersection is used as the denominator. Ifomit
is chosen, then the percentage is omitted.- 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
# Preparation of the test case - use `EOSDY` and `DCSREAS` variables to demonstrate missing data.
data <- teal_data()
data <- within(data, {
ADSL <- tmc_ex_adsl
ADSL$EOSDY[1] <- NA_integer_
})
join_keys(data) <- default_cdisc_join_keys[names(data)]
ADSL <- data[["ADSL"]]
app <- init(
data = data,
modules = modules(
tm_t_summary(
label = "Demographic Table",
dataname = "ADSL",
arm_var = choices_selected(c("ARM", "ARMCD"), "ARM"),
add_total = TRUE,
summarize_vars = choices_selected(
c("SEX", "RACE", "BMRKR2", "EOSDY", "DCSREAS", "AGE"),
c("SEX", "RACE")
),
useNA = "ifany"
)
)
)
#> Initializing tm_t_summary
#> Initializing reporter_previewer_module
if (interactive()) {
shinyApp(app$ui, app$server)
}