tm_a_mmrm {teal.modules.clinical}

teal Module: Mixed Model Repeated Measurements (MMRM) Analysis

Description

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 to ADSL.

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 as arm_var. It defines the grouping variable(s) in the results table. If there are two elements selected for arm_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 as visit variable. Must be a factor in dataname.

cov_var

(teal.transform::choices_selected())
object with all available choices and preselected option for the covariates variables.

arm_ref_comp

(list) optional,
if specified it must be a named list with each element corresponding to an arm variable in ADSL and the element must be another list (possibly with delayed teal.transform::variable_choices() or delayed teal.transform::value_choices() with the elements named ref and comp that 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 from dataname.

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

(numeric) optional
vector of length three with c(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

(numeric) optional
vector of length three with c(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 (see add_total). Defaults to "All Patients". To set a new default total_label to apply in all modules, run set_default_total_label("new_default").

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 the shiny::helpText() elements are useful.

basic_table_args

(basic_table_args) optional
object created by teal.widgets::basic_table_args() with settings for the module table. The argument is merged with option teal.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").

ggplot2_args

(ggplot2_args) optional
object created by teal.widgets::ggplot2_args() with settings for all the plots or named list of ggplot2_args objects for plot-specific settings. List names should match the following: c("default", "lsmeans", "diagnostic"). The argument is merged with option teal.ggplot2_args and with default module arguments (hard coded in the module body). For more details, see the help vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets").

Value

a teal_module object.

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)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}