Nothing
#' Template: Summarize Variables by Row Groups Module
#'
#' Creates a valid expression to generate a table to summarize variables by row groups.
#'
#' @inheritParams template_arguments
#' @param parallel_vars (`logical`)\cr whether summarized variables should be arranged in columns. Can only be set to
#' `TRUE` if all chosen analysis variables are numeric.
#' @param row_groups (`logical`)\cr whether summarized variables should be arranged in row groups.
#' @param drop_zero_levels (`logical`)\cr whether rows with zero counts in all columns should be removed from the table.
#'
#' @inherit template_arguments return
#'
#' @seealso [tm_t_summary_by()]
#'
#' @keywords internal
template_summary_by <- function(parentname,
dataname,
arm_var,
id_var,
sum_vars,
by_vars,
var_labels = character(),
add_total = TRUE,
total_label = default_total_label(),
parallel_vars = FALSE,
row_groups = FALSE,
na.rm = FALSE, # nolint: object_name.
na_level = default_na_str(),
numeric_stats = c(
"n", "mean_sd", "mean_ci", "median", "median_ci", "quantiles", "range"
),
denominator = c("N", "n", "omit"),
drop_arm_levels = TRUE,
drop_zero_levels = TRUE,
basic_table_args = teal.widgets::basic_table_args()) {
checkmate::assert_string(parentname)
checkmate::assert_string(dataname)
checkmate::assert_string(id_var)
checkmate::assert_character(sum_vars)
checkmate::assert_character(by_vars)
checkmate::assert_character(var_labels)
checkmate::assert_flag(add_total)
checkmate::assert_string(total_label)
checkmate::assert_flag(parallel_vars)
checkmate::assert_flag(row_groups)
checkmate::assert_flag(na.rm)
checkmate::assert_string(na_level)
checkmate::assert_flag(drop_arm_levels)
checkmate::assert_character(numeric_stats)
checkmate::assert_flag(drop_zero_levels)
checkmate::assert_character(arm_var, min.len = 1, max.len = 2)
denominator <- match.arg(denominator)
y <- list()
# Data processing
data_list <- list()
data_list <- add_expr(
data_list,
substitute(
expr = anl <- df %>%
df_explicit_na(omit_columns = setdiff(names(df), c(by_vars, sum_vars)), na_level = na_str),
env = list(
df = as.name(dataname),
by_vars = by_vars,
sum_vars = sum_vars,
na_str = na_level
)
)
)
prepare_arm_levels_call <- lapply(arm_var, function(x) {
prepare_arm_levels(
dataname = "anl",
parentname = parentname,
arm_var = x,
drop_arm_levels = drop_arm_levels
)
})
data_list <- Reduce(add_expr, prepare_arm_levels_call, init = data_list)
data_list <- add_expr(
data_list,
substitute(
expr = parentname <- df_explicit_na(parentname, na_level = na_str),
env = list(parentname = as.name(parentname), na_str = na_level)
)
)
y$data <- bracket_expr(data_list)
# Build layout
y$layout_prep <- quote(split_fun <- drop_split_levels)
if (row_groups) {
y$layout_cfun <- quote(
cfun_unique <- function(x, labelstr = "", .N_col) { # nolint: object_name.
y <- length(unique(x))
rcell(
c(y, y / .N_col),
label = labelstr
)
}
)
}
table_title <- paste("Summary Table for", paste(sum_vars, collapse = ", "), "by", paste(by_vars, collapse = ", "))
parsed_basic_table_args <- teal.widgets::parse_basic_table_args(
teal.widgets::resolve_basic_table_args(
user_table = basic_table_args,
module_table = teal.widgets::basic_table_args(show_colcounts = TRUE, title = table_title)
)
)
layout_list <- list()
layout_list <- add_expr(
layout_list,
parsed_basic_table_args
)
split_cols_call <- lapply(arm_var, function(x) {
if (drop_arm_levels) {
substitute(
expr = rtables::split_cols_by(x, split_fun = drop_split_levels),
env = list(x = x)
)
} else {
substitute(
expr = rtables::split_cols_by(x),
env = list(x = x)
)
}
})
layout_list <- Reduce(add_expr, split_cols_call, init = layout_list)
if (add_total && !parallel_vars) {
layout_list <- add_expr(
layout_list,
substitute(
expr = rtables::add_overall_col(total_label),
env = list(total_label = total_label)
)
)
}
env_vars <- list(
sum_vars = sum_vars,
sum_var_labels = var_labels[sum_vars],
na.rm = na.rm,
na_level = na_level,
denom = ifelse(denominator == "n", "n", "N_col"),
stats = c(
numeric_stats,
ifelse(denominator == "omit", "count", "count_fraction")
)
)
for (by_var in by_vars) {
split_label <- substitute(
expr = teal.data::col_labels(dataname, fill = FALSE)[[by_var]],
env = list(
dataname = as.name(dataname),
by_var = by_var
)
)
layout_list <- add_expr(
layout_list,
substitute(
rtables::split_rows_by(
by_var,
split_label = split_label,
split_fun = split_fun,
label_pos = "topleft"
),
env = list(
by_var = by_var,
split_label = split_label
)
)
)
if (row_groups) {
layout_list <- add_expr(
layout_list,
substitute(
expr = rtables::summarize_row_groups(var = id_var, cfun = cfun_unique, na_str = na_str),
env = list(
id_var = id_var,
na_str = na_level
)
)
)
}
}
if (parallel_vars) {
layout_list <- add_expr(
layout_list,
if (length(var_labels) > 0) {
substitute(
expr = split_cols_by_multivar(vars = sum_vars, varlabels = sum_var_labels),
env = list(sum_vars = sum_vars, sum_var_labels = var_labels[sum_vars])
)
} else {
substitute(
expr = split_cols_by_multivar(vars = sum_vars),
env = list(sum_vars = sum_vars)
)
}
)
}
if (row_groups) {
layout_list <- layout_list
} else {
layout_list <- add_expr(
layout_list,
if (parallel_vars) {
if (length(var_labels) > 0) {
substitute(
expr = summarize_colvars(
na.rm = na.rm,
denom = denom,
.stats = stats,
na_str = na_level
),
env = env_vars
)
} else {
substitute(
expr = summarize_colvars(
vars = sum_vars,
na.rm = na.rm,
denom = denom,
.stats = stats,
na_str = na_level
),
env = env_vars
)
}
} else {
if (length(var_labels > 0)) {
substitute(
expr = analyze_vars(
vars = sum_vars,
var_labels = sum_var_labels,
na.rm = na.rm,
na_str = na_level,
denom = denom,
.stats = stats
),
env = env_vars
)
} else {
substitute(
expr = analyze_vars(
vars = sum_vars,
na.rm = na.rm,
na_str = na_level,
denom = denom,
.stats = stats
),
env = env_vars
)
}
}
)
}
y$layout <- substitute(
expr = lyt <- layout_pipe,
env = list(layout_pipe = pipe_expr(layout_list))
)
if (drop_zero_levels) {
y$table <- substitute(
expr = {
all_zero <- function(tr) {
if (!inherits(tr, "TableRow") || inherits(tr, "LabelRow")) {
return(FALSE)
}
rvs <- unlist(unname(row_values(tr)))
isTRUE(all(rvs == 0))
}
table <- rtables::build_table(
lyt = lyt,
df = anl,
alt_counts_df = parent
) %>% rtables::trim_rows(criteria = all_zero)
},
env = list(parent = as.name(parentname))
)
} else {
y$table <- substitute(
expr = {
table <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = parent)
},
env = list(parent = as.name(parentname))
)
}
y
}
#' teal Module: Summarize Variables by Row Groups
#'
#' This module produces a table to summarize variables by row groups.
#'
#' @inheritParams module_arguments
#' @inheritParams teal::module
#' @inheritParams template_summary_by
#' @param arm_var ([teal.transform::choices_selected()])\cr 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.
#'
#' @inherit module_arguments return seealso
#'
#' @section Decorating Module:
#'
#' 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_summary_by(
#' ..., # 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.
#'
#' @examplesShinylive
#' library(teal.modules.clinical)
#' interactive <- function() TRUE
#' {{ next_example }}
#'
#' @examples
#' data <- teal_data()
#' data <- within(data, {
#' ADSL <- tmc_ex_adsl
#' ADLB <- tmc_ex_adlb
#' })
#' join_keys(data) <- default_cdisc_join_keys[names(data)]
#'
#' ADSL <- data[["ADSL"]]
#' ADLB <- data[["ADLB"]]
#'
#' app <- init(
#' data = data,
#' modules = modules(
#' tm_t_summary_by(
#' label = "Summary by Row Groups Table",
#' dataname = "ADLB",
#' arm_var = choices_selected(
#' choices = variable_choices(ADSL, c("ARM", "ARMCD")),
#' selected = "ARM"
#' ),
#' add_total = TRUE,
#' by_vars = choices_selected(
#' choices = variable_choices(ADLB, c("PARAM", "AVISIT")),
#' selected = c("AVISIT")
#' ),
#' summarize_vars = choices_selected(
#' choices = variable_choices(ADLB, c("AVAL", "CHG")),
#' selected = c("AVAL")
#' ),
#' useNA = "ifany",
#' paramcd = choices_selected(
#' choices = value_choices(ADLB, "PARAMCD", "PARAM"),
#' selected = "ALT"
#' )
#' )
#' )
#' )
#' if (interactive()) {
#' shinyApp(app$ui, app$server)
#' }
#'
#' @export
tm_t_summary_by <- function(label,
dataname,
parentname = ifelse(
inherits(arm_var, "data_extract_spec"),
teal.transform::datanames_input(arm_var),
"ADSL"
),
arm_var,
by_vars,
summarize_vars,
id_var = teal.transform::choices_selected(
teal.transform::variable_choices(dataname, subset = "USUBJID"),
selected = "USUBJID", fixed = TRUE
),
paramcd = NULL,
add_total = TRUE,
total_label = default_total_label(),
parallel_vars = FALSE,
row_groups = FALSE,
useNA = c("ifany", "no"), # nolint: object_name.
na_level = default_na_str(),
numeric_stats = c("n", "mean_sd", "median", "range"),
denominator = teal.transform::choices_selected(c("n", "N", "omit"), "omit", fixed = TRUE),
drop_arm_levels = TRUE,
drop_zero_levels = TRUE,
pre_output = NULL,
post_output = NULL,
basic_table_args = teal.widgets::basic_table_args(),
transformators = list(),
decorators = list()) {
message("Initializing tm_t_summary_by")
checkmate::assert_string(label)
checkmate::assert_string(dataname)
checkmate::assert_string(parentname)
useNA <- match.arg(useNA) # nolint: object_name.
checkmate::assert_string(na_level)
checkmate::assert_class(arm_var, "choices_selected")
checkmate::assert_class(by_vars, "choices_selected")
checkmate::assert_class(summarize_vars, "choices_selected")
checkmate::assert_class(id_var, "choices_selected")
checkmate::assert_class(paramcd, "choices_selected", null.ok = TRUE)
checkmate::assert_class(denominator, "choices_selected")
checkmate::assert_flag(add_total)
checkmate::assert_string(total_label)
checkmate::assert_flag(drop_zero_levels)
checkmate::assert_subset(denominator$choices, choices = c("n", "N", "omit"))
checkmate::assert_flag(parallel_vars)
checkmate::assert_flag(row_groups)
checkmate::assert_flag(drop_arm_levels)
checkmate::assert_character(numeric_stats, min.len = 1)
checkmate::assert_class(pre_output, classes = "shiny.tag", null.ok = TRUE)
checkmate::assert_class(post_output, classes = "shiny.tag", null.ok = TRUE)
checkmate::assert_class(basic_table_args, "basic_table_args")
numeric_stats_choices <- c("n", "mean_sd", "mean_ci", "geom_mean", "median", "median_ci", "quantiles", "range")
numeric_stats <- match.arg(numeric_stats, numeric_stats_choices, several.ok = TRUE)
assert_decorators(decorators, "table")
args <- c(as.list(environment()))
data_extract_list <- list(
arm_var = cs_to_des_select(arm_var, dataname = parentname, multiple = TRUE, ordered = TRUE),
id_var = cs_to_des_select(id_var, dataname = dataname),
paramcd = `if`(
is.null(paramcd),
NULL,
cs_to_des_filter(paramcd, dataname = dataname, multiple = TRUE)
),
by_vars = cs_to_des_select(by_vars, dataname = dataname, multiple = TRUE, ordered = TRUE),
summarize_vars = cs_to_des_select(summarize_vars, dataname = dataname, multiple = TRUE, ordered = TRUE)
)
module(
label = label,
ui = ui_summary_by,
ui_args = c(data_extract_list, args),
server = srv_summary_by,
server_args = c(
data_extract_list,
list(
dataname = dataname,
parentname = parentname,
label = label,
total_label = total_label,
na_level = na_level,
basic_table_args = basic_table_args,
decorators = decorators
)
),
transformators = transformators,
datanames = teal.transform::get_extract_datanames(data_extract_list)
)
}
#' @keywords internal
ui_summary_by <- function(id, ...) {
ns <- NS(id)
a <- list(...)
is_single_dataset_value <- teal.transform::is_single_dataset(
a$arm_var,
a$id_var,
a$paramcd,
a$by_vars,
a$summarize_vars
)
teal.widgets::standard_layout(
output = teal.widgets::white_small_well(teal.widgets::table_with_settings_ui(ns("table"))),
encoding = tags$div(
### Reporter
teal.reporter::simple_reporter_ui(ns("simple_reporter")),
###
tags$label("Encodings", class = "text-primary"),
teal.transform::datanames_input(a[c("arm_var", "id_var", "paramcd", "by_vars", "summarize_vars")]),
teal.transform::data_extract_ui(
id = ns("arm_var"),
label = "Select Column Variable(s)",
data_extract_spec = a$arm_var,
is_single_dataset = is_single_dataset_value
),
checkboxInput(ns("add_total"), "Add All Patients column", value = a$add_total),
`if`(
is.null(a$paramcd),
NULL,
teal.transform::data_extract_ui(
id = ns("paramcd"),
label = "Select Endpoint",
data_extract_spec = a$paramcd,
is_single_dataset = is_single_dataset_value
)
),
teal.transform::data_extract_ui(
id = ns("by_vars"),
label = "Row By Variable",
data_extract_spec = a$by_vars,
is_single_dataset = is_single_dataset_value
),
teal.transform::data_extract_ui(
id = ns("summarize_vars"),
label = "Summarize Variables",
data_extract_spec = a$summarize_vars,
is_single_dataset = is_single_dataset_value
),
checkboxInput(ns("parallel_vars"), "Show summarize variables in parallel", value = a$parallel_vars),
checkboxInput(ns("row_groups"), "Summarize number of subjects in row groups", value = a$row_groups),
teal.widgets::panel_group(
teal.widgets::panel_item(
"Additional table settings",
checkboxInput(ns("drop_zero_levels"), "Drop rows with 0 count", value = a$drop_zero_levels),
radioButtons(
ns("useNA"),
label = "Display NA counts",
choices = c("ifany", "no"),
selected = a$useNA
),
teal.widgets::optionalSelectInput(
inputId = ns("denominator"),
label = "Denominator choice",
choices = a$denominator$choices,
selected = a$denominator$selected,
fixed = a$denominator$fixed
),
checkboxGroupInput(
ns("numeric_stats"),
label = "Choose the statistics to display for numeric variables",
choices = c(
"n" = "n",
"Mean (SD)" = "mean_sd",
"Mean 95% CI" = "mean_ci",
"Geometric Mean" = "geom_mean",
"Median" = "median",
"Median 95% CI" = "median_ci",
"25% and 75%-ile" = "quantiles",
"Min - Max" = "range"
),
selected = a$numeric_stats
),
if (a$dataname == a$parentname) {
shinyjs::hidden(
checkboxInput(
ns("drop_arm_levels"),
label = "it's a BUG if you see this",
value = TRUE
)
)
} else {
checkboxInput(
ns("drop_arm_levels"),
label = sprintf("Drop columns not in filtered %s", a$dataname),
value = a$drop_arm_levels
)
}
)
),
ui_decorate_teal_data(ns("decorator"), decorators = select_decorators(a$decorators, "table")),
teal.widgets::panel_group(
teal.widgets::panel_item(
"Additional Variables Info",
teal.transform::data_extract_ui(
id = ns("id_var"),
label = "Subject Identifier",
data_extract_spec = a$id_var,
is_single_dataset = is_single_dataset_value
)
)
)
),
forms = tagList(
teal.widgets::verbatim_popup_ui(ns("rcode"), button_label = "Show R code")
),
pre_output = a$pre_output,
post_output = a$post_output
)
}
#' @keywords internal
srv_summary_by <- function(id,
data,
reporter,
filter_panel_api,
dataname,
parentname,
arm_var,
id_var,
paramcd,
by_vars,
summarize_vars,
add_total,
total_label,
na_level,
drop_arm_levels,
drop_zero_levels,
label,
basic_table_args,
decorators) {
with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
with_filter <- !missing(filter_panel_api) && inherits(filter_panel_api, "FilterPanelAPI")
checkmate::assert_class(data, "reactive")
checkmate::assert_class(shiny::isolate(data()), "teal_data")
moduleServer(id, function(input, output, session) {
teal.logger::log_shiny_input_changes(input, namespace = "teal.modules.clinical")
vars <- list(arm_var = arm_var, id_var = id_var, summarize_vars = summarize_vars, by_vars = by_vars)
if (!is.null(paramcd)) {
vars[["paramcd"]] <- paramcd
}
validation_rules <- list(
arm_var = ~ if (length(.) != 1 && length(.) != 2) {
"Please select 1 or 2 column variables"
},
id_var = shinyvalidate::sv_required("Please select a subject identifier."),
summarize_vars = shinyvalidate::sv_required("Please select a summarize variable.")
)
selector_list <- teal.transform::data_extract_multiple_srv(
data_extract = vars,
datasets = data,
select_validation_rule = validation_rules,
filter_validation_rule = list(paramcd = shinyvalidate::sv_required(message = "Please select a filter."))
)
iv_r <- reactive({
iv <- shinyvalidate::InputValidator$new()
iv$add_rule("numeric_stats", shinyvalidate::sv_required("Please select at least one statistic to display."))
teal.transform::compose_and_enable_validators(iv, selector_list)
})
anl_inputs <- teal.transform::merge_expression_srv(
selector_list = selector_list,
datasets = data,
merge_function = "dplyr::inner_join"
)
adsl_inputs <- teal.transform::merge_expression_module(
id = "adsl_merge",
datasets = data,
data_extract = list(arm_var = arm_var),
anl_name = "ANL_ADSL"
)
anl_q <- reactive({
data() %>%
teal.code::eval_code(as.expression(anl_inputs()$expr)) %>%
teal.code::eval_code(as.expression(adsl_inputs()$expr))
})
merged <- list(
anl_input_r = anl_inputs,
adsl_input_r = adsl_inputs,
anl_q = anl_q
)
# Prepare the analysis environment (filter data, check data, populate envir).
validate_checks <- reactive({
teal::validate_inputs(iv_r())
adsl_filtered <- merged$anl_q()[[parentname]]
anl_filtered <- merged$anl_q()[[dataname]]
input_arm_var <- names(merged$anl_input_r()$columns_source$arm_var)
input_id_var <- names(merged$anl_input_r()$columns_source$id_var)
input_by_vars <- names(merged$anl_input_r()$columns_source$by_vars)
input_summarize_vars <- names(merged$anl_input_r()$columns_source$summarize_var)
input_paramcd <- `if`(is.null(paramcd), NULL, unlist(paramcd$filter)["vars_selected"])
# validate inputs
validate_standard_inputs(
adsl = adsl_filtered,
adslvars = c("USUBJID", "STUDYID", input_arm_var),
anl = anl_filtered,
anlvars = c("USUBJID", "STUDYID", input_paramcd, input_by_vars, input_summarize_vars, input_id_var),
arm_var = input_arm_var[[1]]
)
if (input$parallel_vars) {
validate(shiny::need(
all(vapply(anl_filtered[input_summarize_vars], is.numeric, logical(1))),
"Summarize variables must all be numeric to display in parallel columns."
))
}
})
# Generate r code for the analysis.
all_q <- reactive({
validate_checks()
summarize_vars <- as.vector(merged$anl_input_r()$columns_source$summarize_vars)
var_labels <- teal.data::col_labels(merged$anl_q()[[dataname]][, summarize_vars, drop = FALSE])
my_calls <- template_summary_by(
parentname = "ANL_ADSL",
dataname = "ANL",
arm_var = as.vector(merged$anl_input_r()$columns_source$arm_var),
sum_vars = summarize_vars,
by_vars = as.vector(merged$anl_input_r()$columns_source$by_vars),
var_labels = var_labels,
id_var = as.vector(merged$anl_input_r()$columns_source$id_var),
na.rm = ifelse(input$useNA == "ifany", FALSE, TRUE),
na_level = na_level,
numeric_stats = input$numeric_stats,
denominator = input$denominator,
add_total = input$add_total,
total_label = total_label,
parallel_vars = input$parallel_vars,
row_groups = input$row_groups,
drop_arm_levels = input$drop_arm_levels,
drop_zero_levels = input$drop_zero_levels,
basic_table_args = basic_table_args
)
teal.code::eval_code(merged$anl_q(), as.expression(unlist(my_calls)))
})
# Decoration of table output.
decorated_table_q <- srv_decorate_teal_data(
id = "decorator",
data = all_q,
decorators = select_decorators(decorators, "table"),
expr = table
)
# Outputs to render.
table_r <- reactive(decorated_table_q()[["table"]])
teal.widgets::table_with_settings_srv(
id = "table",
table_r = table_r
)
# Render R code.
source_code_r <- reactive(teal.code::get_code(req(decorated_table_q())))
teal.widgets::verbatim_popup_srv(
id = "rcode",
verbatim_content = source_code_r,
title = label
)
### REPORTER
if (with_reporter) {
card_fun <- function(comment, label) {
card <- teal::report_card_template(
title = "Summarize Variables by Row Groups Table",
label = label,
with_filter = with_filter,
filter_panel_api = filter_panel_api
)
card$append_text("Table", "header3")
card$append_table(table_r())
if (!comment == "") {
card$append_text("Comment", "header3")
card$append_text(comment)
}
card$append_src(source_code_r())
card
}
teal.reporter::simple_reporter_srv("simple_reporter", reporter = reporter, card_fun = card_fun)
}
###
})
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.