View source: R/tm_t_abnormality_by_worst_grade.R
tm_t_abnormality_by_worst_grade | R Documentation |
This module produces a table to summarize laboratory test results with highest grade post-baseline
tm_t_abnormality_by_worst_grade(
label,
dataname,
parentname = ifelse(inherits(arm_var, "data_extract_spec"),
teal.transform::datanames_input(arm_var), "ADSL"),
arm_var,
id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
subset = "USUBJID"), selected = "USUBJID", fixed = TRUE),
paramcd,
atoxgr_var =
teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset =
"ATOXGR"), selected = "ATOXGR", fixed = TRUE),
worst_high_flag_var =
teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset =
"WGRHIFL"), selected = "WGRHIFL", fixed = TRUE),
worst_low_flag_var =
teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset =
"WGRLOFL"), selected = "WGRLOFL", fixed = TRUE),
worst_flag_indicator = teal.transform::choices_selected("Y"),
add_total = TRUE,
total_label = default_total_label(),
drop_arm_levels = TRUE,
pre_output = NULL,
post_output = NULL,
basic_table_args = teal.widgets::basic_table_args(),
transformators = list(),
decorators = list()
)
a teal_module
object.
This module generates the following objects, which can be modified in place using decorators:
table
(TableTree
- output of rtables::build_table()
)
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_t_abnormality_by_worst_grade( ..., # arguments for module decorators = list( table = teal_transform_module(...) # applied only to `table` 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.
The TLG Catalog where additional example apps implementing this module can be found.
library(dplyr)
data <- teal_data()
data <- within(data, {
ADSL <- tmc_ex_adsl
ADLB <- tmc_ex_adlb %>%
filter(!AVISIT %in% c("SCREENING", "BASELINE"))
})
join_keys(data) <- default_cdisc_join_keys[names(data)]
ADSL <- data[["ADSL"]]
ADLB <- data[["ADLB"]]
app <- init(
data = data,
modules = modules(
tm_t_abnormality_by_worst_grade(
label = "Laboratory Test Results with Highest Grade Post-Baseline",
dataname = "ADLB",
arm_var = choices_selected(
choices = variable_choices(ADSL, subset = c("ARM", "ARMCD")),
selected = "ARM"
),
paramcd = choices_selected(
choices = value_choices(ADLB, "PARAMCD", "PARAM"),
selected = c("ALT", "CRP", "IGA")
),
add_total = FALSE
)
),
filter = teal_slices(
teal_slice("ADSL", "SAFFL", selected = "Y"),
teal_slice("ADLB", "ONTRTFL", selected = "Y")
)
)
if (interactive()) {
shinyApp(app$ui, app$server)
}
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