Server logic for the summary table module

Usage

summary_table_server(
  module_id,
  table_dataset,
  pop_dataset,
  subjid_var,
  show_pop_flag_selection = FALSE,
  show_aggregate_method = FALSE,
  show_modal_on_click = TRUE,
  on_sbj_click_fun = function() NULL,
  stats_functions = NULL,
  stats_formats = NULL,
  stats_labels = NULL,
  stats_replace = NULL,
  default_summarize_on = NULL,
  choices_summarize_on = NULL,
  default_group_by = NULL,
  choices_group_by = NULL,
  default_row_by = NULL,
  choices_row_by = NULL,
  default_pop_flags = NULL,
  choices_pop_flags = NULL,
  flagged_row_processing = NULL,
  table_dataset_unfiltered = NULL,
  total_group_val = "Total"
)

Arguments

module_id

[character(1)]

A string that serves as a unique identifier for the module.

table_dataset

[data.frame]

A reactive dataset containing the data for analysis.

pop_dataset

[data.frame]

A reactive dataset containing the population data.

subjid_var

[character(1)]

A string representing the participant identifier column in both datasets.

show_pop_flag_selection

[logical(1)]

A flag to indicate whether to show the population flag selection. Other associated arguments are default_pop_flags and choices_pop_flags.

show_aggregate_method

[logical(1)]

A flag to indicate whether to show (and apply) aggregate methods. If more than one row per participant exists after population grouping and row categorization has been applied then aggreation of those rows can be applied using a selected method. Other associated arguments are default_aggregate_method and choices_aggregate_method.

show_modal_on_click

[logical(1)]

A flag to indicate whether clicking a table cell should display a modal dialog with the participant IDs.

on_sbj_click_fun

[function]

Function to invoke when a participant identifier is clicked.

stats_functions

[list(1+) | NULL]

A named list defining the functions used for summarizing numerical data. The functions must either return a single numeric value (e.g. mean, stats::sd, etc.) or a vector of numeric values (e.g. \(x) stats::quantile(x, c(0.25, 0.75))). Note that the functions will not be applied to empty groupings, but if a function requires more than one data point (e.g. stats::t.test) then the error cases must be dealt with using a wrapper function; see module documentation for further information.

stats_formats

[list(1+) | NULL]

A named list of lists defining the combination and formatting of the function results from summarizing numerical data. Each element lists the argument values passed to sprintf, the result being assigned to the element name (internally corresponding to an interim results data frame column name). The names from the list elements of stats_functions correspond to column names that can be used in the sprintf arguments, but note that if a function returns more than one value, those values must be referred to using a dot followed by an integer suffix, e.g. if the function named meanci returns two values then use "meanci.1", and "meanci.2". The name of each element list should be a keyword conveying the meaning of the combined statistics, e.g. minmax for the minimum to maximum range. The name can also be the same as the name from stats_functions, e.g. meanci for the mean confidence interval.

Any results from functions given in stats_functions that do not appear in the formatting will be automatically formatted as character.

stats_labels

[character(1+) | NULL]

A named vector of statistics labels that should be used in the summary table. The names correspond to the names assigned in the stats_formats list, or otherwise the names in the stats_functions list.

Labels apply to UI statistics checkbox labels and table statistics labels. Note that if a function defined in stats_functions returns more than one value, e.g. stats::quantile, and those values are not combined in stats_formats, then they appear separately in the table statistics, but the UI statistics checkbox will reflect the name given to the function definition. Labels can be applied to both cases; see module documentation for further information.

stats_replace

[list(1+) | NULL]

A named list of lists of list(pattern =, replacement =) pairs defining replacements that should be applied, in order, to the formatted results from stats_formats. pattern is a regular expression matched against the formatted result, and replacement is the string substituted in. The names of the outer list should match the names of the list elements in stats_formats.

default_summarize_on

[character(1+) | NULL]

A vector of variable names from the analysis dataset, used as the default for selected variables to summarize on (optional).

choices_summarize_on

[character(1+) | NULL]

A vector of variable names from the analysis dataset, specifying the possible choices for the variables to summarize on (optional). If it is not specified then all variables from the analysis dataset, excluding Date and POSIXt class variables, will be used.

default_group_by

[character(1+) | NULL]

A vector of variable names from the population dataset, used as the default for selected variables to group by (optional).

choices_group_by

[character(1+) | NULL]

A vector of variable names from the population dataset, specifying the possible choices for the variables to group by (optional). If it is not specified then all factor and character variables from the population dataset will be used.

default_row_by

[character(1+) | NULL]

A vector of variable names from the dataset specified by table_dataset_name, used as the default for selected variables to categorize on (optional).

choices_row_by

[character(1+) | NULL]

A vector of variable names from the analysis dataset, specifying the possible choices for the variables to categorize on (optional). If it is not specified then all factor and character variables from the analysis dataset will be used.

default_pop_flags

[character(1+) | NULL]

A vector of variable names from the population dataset, used as the default for selected population flag variables (optional).

Participants are identified as being within a population when the value of the flag variable is "Y".

choices_pop_flags

[character(1+) | NULL]

A vector of variable names from the population dataset, specifying the possible choices for the population flag variables (optional). If it is not specified then all FL suffixed factor and character variables from the population dataset will be used.

Participants are identified as being within a population when the value of the flag variable is "Y".

flagged_row_processing

[list(1+) | NULL]

A list of lists defining the processing and categorization of flagged rows. If NULL then flagged rows will not be processed. Each sub-list corresponds to a single flag variable, and has the following elements:

flag_var: String naming the flag variable to evaluate (e.g. "LVOTFL").
dependent_vars: A vector of variable names from the analysis dataset, indicating the variables that the flag variable is grouped by (e.g. c("USUBJID", "PARAM")). This ensures global filtering on the analysis dataset is applied to the flagged rows for these dependent variables.
var_assignments: A named list of variable assignments, where names correspond to target dataset columns and values represent the replacement values, e.g. if creating last value on treatment visits, then an example assignment would be AVISIT = "Last value on treatment".

Each flagged row is duplicated with the specified variable assignments applied.

table_dataset_unfiltered

[data.frame | NULL]

A reactive dataset containing the unfiltered analysis data, used for flagged row processing.

total_group_val

[character(1)]

A string indicating the label for the total group column.

Value

A reactive value containing the list of participant identifiers in the clicked cell, if applicable.