This module produces analysis tables and plots for Mixed Model Repeated Measurements.
Usage
tm_a_mmrm(
label,
dataname,
parentname = ifelse(inherits(arm_var, "data_extract_spec"),
teal.transform::datanames_input(arm_var), "ADSL"),
aval_var,
id_var,
arm_var,
visit_var,
cov_var,
arm_ref_comp = NULL,
paramcd,
method = teal.transform::choices_selected(c("Satterthwaite", "Kenward-Roger",
"Kenward-Roger-Linear"), "Satterthwaite", keep_order = TRUE),
conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order =
TRUE),
plot_height = c(700L, 200L, 2000L),
plot_width = NULL,
total_label = default_total_label(),
pre_output = NULL,
post_output = NULL,
basic_table_args = teal.widgets::basic_table_args(),
ggplot2_args = teal.widgets::ggplot2_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.- aval_var
(
teal.transform::choices_selected())
object with all available choices and pre-selected option for the analysis variable.- id_var
(
teal.transform::choices_selected())
object specifying the variable name for subject id.- 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.- visit_var
(
teal.transform::choices_selected())
object with all available choices and preselected option for variable names that can be used asvisitvariable. Must be a factor indataname.- cov_var
(
teal.transform::choices_selected())
object with all available choices and preselected option for the covariates variables.- arm_ref_comp
optional, (
list)
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.- paramcd
(
teal.transform::choices_selected())
object with all available choices and preselected option for the parameter code variable fromdataname.- method
(
teal.transform::choices_selected())
object with all available choices and pre-selected option for the adjustment method.- 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).- plot_height
optional, (
numeric)
a vector of length three withc(value, min, max). Specifies the height of the main plot and renders a slider on the plot to interactively adjust the plot height.- plot_width
optional, (
numeric)
a vector of length three withc(value, min, max). Specifies the width of the main plot and renders a slider on the plot to interactively adjust the plot width.- 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_labelto apply in all modules, runset_default_total_label("new_default").- pre_output
optional, (
shiny.tag)
with text placed before the output to put the output into context. For example a title.- post_output
optional, (
shiny.tag)
with text placed after the output to put the output into context. For example theshiny::helpText()elements are useful.- basic_table_args
optional, (
basic_table_args)
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").- ggplot2_args
(
ggplot2_args)
optional, object created byteal.widgets::ggplot2_args()with settings for all the plots or named list ofggplot2_argsobjects for plot-specific settings. List names should match the following:c("default", "lsmeans", "diagnostic"). The argument is merged with optionteal.ggplot2_argsand with default module arguments (hard coded in the module body). For more details, see the help vignette:vignette("custom-ggplot2-arguments", package = "teal.widgets").
Note
The ordering of the input data sets can lead to slightly different numerical results or
different convergence behavior. This is a known observation with the used package
lme4. However, once convergence is achieved, the results are reliable up to
numerical precision.
See also
The TLG Catalog where additional example apps implementing this module can be found.
Examples
library(dplyr)
arm_ref_comp <- list(
ARMCD = list(
ref = "ARM B",
comp = c("ARM A", "ARM C")
)
)
data <- teal_data()
data <- within(data, {
ADSL <- tmc_ex_adsl
ADQS <- tmc_ex_adqs %>%
filter(ABLFL != "Y" & ABLFL2 != "Y") %>%
filter(AVISIT %in% c("WEEK 1 DAY 8", "WEEK 2 DAY 15", "WEEK 3 DAY 22")) %>%
mutate(
AVISIT = as.factor(AVISIT),
AVISITN = rank(AVISITN) %>%
as.factor() %>%
as.numeric() %>%
as.factor() #' making consecutive numeric factor
)
})
datanames <- c("ADSL", "ADQS")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]
app <- init(
data = data,
modules = modules(
tm_a_mmrm(
label = "MMRM",
dataname = "ADQS",
aval_var = choices_selected(c("AVAL", "CHG"), "AVAL"),
id_var = choices_selected(c("USUBJID", "SUBJID"), "USUBJID"),
arm_var = choices_selected(c("ARM", "ARMCD"), "ARM"),
visit_var = choices_selected(c("AVISIT", "AVISITN"), "AVISIT"),
arm_ref_comp = arm_ref_comp,
paramcd = choices_selected(
choices = value_choices(data[["ADQS"]], "PARAMCD", "PARAM"),
selected = "FKSI-FWB"
),
cov_var = choices_selected(c("BASE", "AGE", "SEX", "BASE:AVISIT"), NULL)
)
)
)
#> [INFO] 2024-02-26 01:42:30.8314 pid:1518 token:[] teal.modules.clinical Initializing tm_a_mmrm
if (interactive()) {
shinyApp(app$ui, app$server)
}