This module produces a table to summarize analysis of variance, consistent with the TLG Catalog
template for AOVT01 available here when multiple
endpoints are selected.
Usage
tm_t_ancova(
label,
dataname,
parentname = ifelse(inherits(arm_var, "data_extract_spec"),
teal.transform::datanames_input(arm_var), "ADSL"),
arm_var,
arm_ref_comp = NULL,
aval_var,
cov_var,
include_interact = FALSE,
interact_var = NULL,
interact_y = FALSE,
avisit,
paramcd,
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()
)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.- arm_ref_comp
(
list) optional,
if specified it must be a named list with each element corresponding to an arm variable inADSLand the element must be another list (possibly with delayedteal.transform::variable_choices()or delayedteal.transform::value_choices()with the elements namedrefandcompthat the defined the default reference and comparison arms when the arm variable is changed.- aval_var
(
teal.transform::choices_selected())
object with all available choices and pre-selected option for the analysis variable.- cov_var
(
teal.transform::choices_selected())
object with all available choices and preselected option for the covariates variables.- include_interact
(
logical)
whether an interaction term should be included in the model.- interact_var
(
character)
name of the variable that should have interactions with arm. If the interaction is not needed, the default option isNULL.- interact_y
(
character)
a selected item from the interact_var column which will be used to select the specificANCOVAresults when interact_var is discrete. If the interaction is not needed, the default option isFALSE.- avisit
(
teal.transform::choices_selected())
value of analysis visitAVISITof interest.- paramcd
(
teal.transform::choices_selected())
object with all available choices and preselected option for the parameter code variable fromdataname.- conf_level
(
teal.transform::choices_selected())
object with all available choices and pre-selected option for the confidence level, each within range of (0, 1).- 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_argsand with default module arguments (hard coded in the module body). For more details, see the vignette:vignette("custom-basic-table-arguments", package = "teal.widgets").- transformators
(
listofteal_transform_module) that will be applied to transform module's data input. To learn more checkvignette("transform-input-data", package = "teal").- decorators
-
(named
listof lists ofteal_transform_module) optional, decorator for tables or plots included in the module output reported. The decorators are applied to the respective output objects.See section "Decorating Module" below for more details.
Details
When a single endpoint is selected, both unadjusted and adjusted comparison are provided. This modules expects that the analysis data has the following variables:
AVISIT: variable used to filter for analysis visits.PARAMCD: variable used to filter for endpoints, after filtering forparamcdandavisit, one observation per patient is expected for the analysis to be meaningful.
Decorating Module
This module generates the following objects, which can be modified in place using decorators:
table(TableTree- output ofrtables::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_ancova(
..., # 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.
See also
The TLG Catalog where additional example apps implementing this module can be found.
Examples
data <- teal_data()
data <- within(data, {
ADSL <- tmc_ex_adsl
ADQS <- tmc_ex_adqs
})
join_keys(data) <- default_cdisc_join_keys[names(data)]
ADSL <- data[["ADSL"]]
ADQS <- data[["ADQS"]]
arm_ref_comp <- list(
ARM = list(
ref = "B: Placebo",
comp = c("A: Drug X", "C: Combination")
),
ACTARMCD = list(
ref = "ARM B",
comp = c("ARM A", "ARM C")
)
)
app <- init(
data = data,
modules = modules(
tm_t_ancova(
label = "ANCOVA Table",
dataname = "ADQS",
avisit = choices_selected(
choices = value_choices(ADQS, "AVISIT"),
selected = "WEEK 1 DAY 8"
),
arm_var = choices_selected(
choices = variable_choices(ADSL, c("ARM", "ACTARMCD", "ARMCD")),
selected = "ARMCD"
),
arm_ref_comp = arm_ref_comp,
aval_var = choices_selected(
choices = variable_choices(ADQS, c("CHG", "AVAL")),
selected = "CHG"
),
cov_var = choices_selected(
choices = variable_choices(ADQS, c("BASE", "STRATA1", "SEX")),
selected = "STRATA1"
),
paramcd = choices_selected(
choices = value_choices(ADQS, "PARAMCD", "PARAM"),
selected = "FKSI-FWB"
),
interact_var = choices_selected(
choices = variable_choices(ADQS, c("BASE", "STRATA1", "SEX")),
selected = "STRATA1"
)
)
)
)
#> Initializing tm_t_ancova
if (interactive()) {
shinyApp(app$ui, app$server)
}