View source: R/tm_t_logistic.R
tm_t_logistic | R Documentation |
This module produces a multi-variable logistic regression table consistent with the TLG Catalog template
LGRT02
available here.
tm_t_logistic(
label,
dataname,
parentname = ifelse(inherits(arm_var, "data_extract_spec"),
teal.transform::datanames_input(arm_var), "ADSL"),
arm_var = NULL,
arm_ref_comp = NULL,
paramcd,
cov_var = NULL,
avalc_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
"AVALC"), "AVALC", fixed = TRUE),
conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order =
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_logistic( ..., # 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
ADRS <- tmc_ex_adrs %>%
filter(PARAMCD %in% c("BESRSPI", "INVET"))
})
join_keys(data) <- default_cdisc_join_keys[names(data)]
ADSL <- data[["ADSL"]]
ADRS <- data[["ADRS"]]
arm_ref_comp <- list(
ACTARMCD = list(
ref = "ARM B",
comp = c("ARM A", "ARM C")
),
ARM = list(
ref = "B: Placebo",
comp = c("A: Drug X", "C: Combination")
)
)
app <- init(
data = data,
modules = modules(
tm_t_logistic(
label = "Logistic Regression",
dataname = "ADRS",
arm_var = choices_selected(
choices = variable_choices(ADRS, c("ARM", "ARMCD")),
selected = "ARM"
),
arm_ref_comp = arm_ref_comp,
paramcd = choices_selected(
choices = value_choices(ADRS, "PARAMCD", "PARAM"),
selected = "BESRSPI"
),
cov_var = choices_selected(
choices = c("SEX", "AGE", "BMRKR1", "BMRKR2"),
selected = "SEX"
)
)
)
)
if (interactive()) {
shinyApp(app$ui, app$server)
}
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