Package 'redcap' reference manual

Title:	R Utilities For REDCap
Description:	R utilities for interacting with the REDCap API.
Authors:	Patrick Barks [aut, cre]
Maintainer:	Patrick Barks <[email protected]>
License:	MIT + file LICENSE
Version:	0.2.0
Built:	2024-10-28 11:20:28 UTC
Source:	https://github.com/epicentre-msf/redcap

Delete records from a REDCap project

Description

Delete records from a REDCap project

Usage

delete_records(conn, records)
delete_records(conn, records)

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`records`	Character vector of record IDs to delete

Value

An integer, the number of records successfully deleted

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

# delete all records associated with IDs "P004" and "P007"
delete_records(conn, records = c("P004", "P007"))

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

# delete all records associated with IDs "P004" and "P007"
delete_records(conn, records = c("P004", "P007"))

## End(Not run)

Fetch records from multiple REDCap forms, returning separate list elements for each form

Description

Wrapper to fetch_records that's vectorized over forms (i.e. instruments). Returns a list whose elements are tibble-style data frames corresponding to each requested form.

Usage

fetch_database(
  conn,
  forms = NULL,
  names_fn = function(x) x,
  records = NULL,
  records_omit = NULL,
  id_field = TRUE,
  rm_empty = TRUE,
  value_labs = TRUE,
  value_labs_fetch_raw = FALSE,
  header_labs = FALSE,
  checkbox_labs = FALSE,
  use_factors = FALSE,
  times_chron = TRUE,
  date_range_begin = NULL,
  date_range_end = NULL,
  fn_dates = parse_date,
  fn_dates_args = list(orders = c("Ymd", "dmY")),
  fn_datetimes = lubridate::parse_date_time,
  fn_datetimes_args = list(orders = c("Ymd HMS", "Ymd HM")),
  na = c("", "NA"),
  dag = TRUE,
  batch_size = 100L,
  batch_delay = 0.5,
  form_delay = 0.5,
  double_resolve = FALSE,
  double_remove = FALSE,
  double_sep = "--",
  fns = NULL
)
fetch_database(
  conn,
  forms = NULL,
  names_fn = function(x) x,
  records = NULL,
  records_omit = NULL,
  id_field = TRUE,
  rm_empty = TRUE,
  value_labs = TRUE,
  value_labs_fetch_raw = FALSE,
  header_labs = FALSE,
  checkbox_labs = FALSE,
  use_factors = FALSE,
  times_chron = TRUE,
  date_range_begin = NULL,
  date_range_end = NULL,
  fn_dates = parse_date,
  fn_dates_args = list(orders = c("Ymd", "dmY")),
  fn_datetimes = lubridate::parse_date_time,
  fn_datetimes_args = list(orders = c("Ymd HMS", "Ymd HM")),
  na = c("", "NA"),
  dag = TRUE,
  batch_size = 100L,
  batch_delay = 0.5,
  form_delay = 0.5,
  double_resolve = FALSE,
  double_remove = FALSE,
  double_sep = "--",
  fns = NULL
)

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`forms`	Character vector of forms (i.e. instruments) to fetch data for. Set to `NULL` (the default) to fetch all forms in the project.
`names_fn`	Function for creating custom list element names given a vector of form names. Defaults to an identity function in which case element names will correspond exactly to form names.
`records`	Character vector of record IDs to fetch. Set to `NULL` (the default) to fetch all record IDs corresponding to the selected form(s).
`records_omit`	Character vector of record IDs to ignore. Set to `NULL` (the default) to not ignore any records. If a given record ID appears in both argument `records` and `records_omit`, argument `records_omit` takes precedence and that record will not be returned.
`id_field`	Logical indicating whether to always include the 'record ID' field (defined in REDCap to be the first variable in the project codebook) in the API request, even if it's not specified in argument `fields`. Defaults to `TRUE`. The record ID field is defined within the first form of a REDCap project, and so API requests for other forms will not include the record ID field by default (unless it's explicitly requested with argument `fields`). The `id_field` argument is a shortcut to avoid having to always explicitly request the record ID field.
`rm_empty`	Logical indicating whether to remove rows for which all fields from the relevant form(s) are missing. See section Removing empty rows. Defaults to `TRUE`.
`value_labs`	Logical indicating whether to return value labels (`TRUE`) or raw values (`FALSE`) for categorical REDCap variables (radio, dropdown, yesno, checkbox). Defaults to `TRUE` to return labels.
`value_labs_fetch_raw`	Logical indicating whether to request raw values for categorical REDCap variables (radio, dropdown, yesno, checkbox), which are then transformed to labels in a separate step when `value_labs = TRUE`. Primarily used for troubleshooting issues with the REDCap API returning fewer records than expected when given certain combinations of request parameters.
`header_labs`	Logical indicating whether to export column names as labels (`TRUE`) or raw variable names (`FALSE`). Defaults to `FALSE` to return raw variable names.
`checkbox_labs`	Logical indicating whether to export checkbox labels (`TRUE`) or statuses (i.e. "Unchecked" or "Checked") (`FALSE`). Defaults to `FALSE` to export statuses. Note this argument is only relevant when `value_labs` is `TRUE` — if `value_labs` is `FALSE` checkbox variables will always be exported as raw values (usually "0"/"1").
`use_factors`	Logical indicating whether categorical REDCap variables (radio, dropdown, yesno, checkbox) should be returned as factors. Factor levels can either be raw values (e.g. "0"/"1") or labels (e.g. "No"/"Yes") depending on arguments `value_labs` and `checkbox_labs`. Defaults to `FALSE`.
`times_chron`	Logical indicating whether to reclass time variables using chron::times (`TRUE`) or leave as character HH:MM format (`FALSE`). Defaults to `TRUE`. Note this only applies to variables of REDCap type "Time (HH:MM)", and not "Time (MM:SS)".
`date_range_begin`	Fetch only records created or modified after a given date-time. Use format "YYYY-MM-DD HH:MM:SS" (e.g., "2017-01-01 00:00:00" for January 1, 2017 at midnight server time). Defaults to NULL to omit a lower time limit.
`date_range_end`	Fetch only records created or modified before a given date-time. Use format "YYYY-MM-DD HH:MM:SS" (e.g., "2017-01-01 00:00:00" for January 1, 2017 at midnight server time). Defaults to NULL to omit a lower time limit.
`fn_dates`	Function to parse REDCap date variables. Defaults to `parse_date`, an internal wrapper to `lubridate::parse_date_time`. If date variables have been converted to numeric (e.g. by writing to Excel), set to e.g. `lubridate::as_date` to convert back to dates.
`fn_dates_args`	List of arguments to pass to `fn_dates`. Can set to empty list `list()` if using a function that doesn't take any arguments.
`fn_datetimes`	Function to parse REDCap datetime variables. Defaults to `lubridate::parse_date_time`.
`fn_datetimes_args`	List of arguments to pass to `fn_datetimes`. Can set to empty list `list()` if using a function that doesn't take any arguments.
`na`	Character vector of strings to interpret as missing values. Passed to readr::read_csv. Defaults to `c("", "NA")`.
`dag`	Logical indicating whether to export the `redcap_data_access_group` field (if used in the project). Defaults to `TRUE`.
`batch_size`	Number of records to fetch per batch. Defaults to `100L`. Set to `Inf` or `NA` to fetch all records at once.
`batch_delay`	Delay in seconds between fetching successive batches, to give the REDCap server time to respond to other requests. Defaults to `0.5`.
`form_delay`	Delay in seconds between fetching successive forms, to give the REDCap server time to respond to other requests. Defaults to `0.5`.
`double_resolve`	Logical indicating whether to resolve double-entries (i.e. records entered in duplicate using REDCap's Double Data Entry module), by filtering to the lowest entry number associated with each unique record. If a project uses double-entry, the record IDs returned by an "Export Records" API request will be a concatenation of the normal record ID and the entry number (1 or 2), normally separated by "–" (e.g. "P0285–1"). To resolve double entries we move the entry number portion of the ID to its own column (`entry`), identify all entries belonging to the same unique record, and retain only the row with the lowest entry number for each unique record. Unique records are identified using the record ID column (after separating the entry number portion), and any of the following columns when present (accounting for argument `header_labs`): redcap_event_name (Redcap Event), redcap_repeat_instrument (Repeat Instrument), redcap_repeat_instance (Repeat Instance).
`double_remove`	Logical indicating whether to remove double-entries (i.e. records entered in duplicate using REDCap's Double Data Entry module), by filtering out records where the record ID field contains pattern `double_sep` (see next argument), so that only merged records remain.
`double_sep`	If `double_resolve` is `TRUE`, the string separator used to split the record ID field into the record ID and entry number. Defaults to "–".
`fns`	Optional list of one or more functions to apply to each list element (i.e. each form). Could be used e.g. to filter out record IDs from test entries, create derived variables, etc. Each function should take a data frame returned by `fetch_records` as its first argument.

Value

A list of tibble-style data frames corresponding to each of the requested forms.

Removing empty rows

Depending on the database design, an "Export Records" API request can sometimes return empty rows, representing forms for which no data has been collected. For example, if forms F1 and F2 are part of the same event, and participant "P001" has form data for F2 but not F1, an API request for F1 will include a row for participant "P001" where all F1-specific fields are empty.

If argument rm_empty is TRUE (the default), fetch_records() will filter out such rows. The check for empty rows is based only on fields that are specific to the form(s) specified in argument forms — i.e. it excludes the record ID field, and generic fields like redcap_event_name, redcap_data_access_group, etc. The check for empty rows also accounts for checkbox fields, which, if argument checkbox_labs is FALSE, will be set to "Unchecked" in an empty form (rather than missing per se).

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

fetch_database(
  conn,
  forms = c("my_form1", "my_form2", "my_form3")
)

# use a custom fn to format the 'participant_id' column of each form
# the function must take a data frame as its first argument
format_ids <- function(x) {
  x$participant_id <- toupper(x$participant_id)
  x$participant_id <- gsub("[^[:alnum:]]+", "_", x$participant_id)
  x
}

fetch_database(
  conn,
  forms = c("my_form1", "my_form2", "my_form3"),
  fns = list(format_ids)
)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

fetch_database(
  conn,
  forms = c("my_form1", "my_form2", "my_form3")
)

# use a custom fn to format the 'participant_id' column of each form
# the function must take a data frame as its first argument
format_ids <- function(x) {
  x$participant_id <- toupper(x$participant_id)
  x$participant_id <- gsub("[^[:alnum:]]+", "_", x$participant_id)
  x
}

fetch_database(
  conn,
  forms = c("my_form1", "my_form2", "my_form3"),
  fns = list(format_ids)
)

## End(Not run)

Fetch records for a REDCap project

Description

Execute an "Export Records" API request to fetch a tibble-style data frame containing records for one or more REDCap instruments.

Usage

fetch_records(
  conn,
  forms = NULL,
  events = NULL,
  records = NULL,
  records_omit = NULL,
  fields = NULL,
  id_field = TRUE,
  rm_empty = TRUE,
  value_labs = TRUE,
  value_labs_fetch_raw = FALSE,
  header_labs = FALSE,
  checkbox_labs = FALSE,
  use_factors = FALSE,
  times_chron = TRUE,
  date_range_begin = NULL,
  date_range_end = NULL,
  fn_dates = parse_date,
  fn_dates_args = list(orders = c("Ymd", "dmY")),
  fn_datetimes = lubridate::parse_date_time,
  fn_datetimes_args = list(orders = c("Ymd HMS", "Ymd HM")),
  na = c("", "NA"),
  dag = TRUE,
  batch_size = 100L,
  batch_delay = 0.5,
  double_resolve = FALSE,
  double_remove = FALSE,
  double_sep = "--"
)
fetch_records(
  conn,
  forms = NULL,
  events = NULL,
  records = NULL,
  records_omit = NULL,
  fields = NULL,
  id_field = TRUE,
  rm_empty = TRUE,
  value_labs = TRUE,
  value_labs_fetch_raw = FALSE,
  header_labs = FALSE,
  checkbox_labs = FALSE,
  use_factors = FALSE,
  times_chron = TRUE,
  date_range_begin = NULL,
  date_range_end = NULL,
  fn_dates = parse_date,
  fn_dates_args = list(orders = c("Ymd", "dmY")),
  fn_datetimes = lubridate::parse_date_time,
  fn_datetimes_args = list(orders = c("Ymd HMS", "Ymd HM")),
  na = c("", "NA"),
  dag = TRUE,
  batch_size = 100L,
  batch_delay = 0.5,
  double_resolve = FALSE,
  double_remove = FALSE,
  double_sep = "--"
)

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`forms`	Character vector of forms (i.e. instruments) to fetch data for. Set to `NULL` (the default) to fetch all forms in the project.
`events`	Character vector of events to fetch. Must correspond to the selected `forms`. Set to `NULL` (the default) to fetch all events corresponding to the selected form(s).
`records`	Character vector of record IDs to fetch. Set to `NULL` (the default) to fetch all record IDs corresponding to the selected form(s).
`records_omit`	Character vector of record IDs to ignore. Set to `NULL` (the default) to not ignore any records. If a given record ID appears in both argument `records` and `records_omit`, argument `records_omit` takes precedence and that record will not be returned.
`fields`	Character vector of fields (i.e. variables) to fetch. Set to `NULL` (the default) to fetch all fields corresponding to the selected form(s).
`id_field`	Logical indicating whether to always include the 'record ID' field (defined in REDCap to be the first variable in the project codebook) in the API request, even if it's not specified in argument `fields`. Defaults to `TRUE`. The record ID field is defined within the first form of a REDCap project, and so API requests for other forms will not include the record ID field by default (unless it's explicitly requested with argument `fields`). The `id_field` argument is a shortcut to avoid having to always explicitly request the record ID field.
`rm_empty`	Logical indicating whether to remove rows for which all fields from the relevant form(s) are missing. See section Removing empty rows. Defaults to `TRUE`.
`value_labs`	Logical indicating whether to return value labels (`TRUE`) or raw values (`FALSE`) for categorical REDCap variables (radio, dropdown, yesno, checkbox). Defaults to `TRUE` to return labels.
`value_labs_fetch_raw`	Logical indicating whether to request raw values for categorical REDCap variables (radio, dropdown, yesno, checkbox), which are then transformed to labels in a separate step when `value_labs = TRUE`. Primarily used for troubleshooting issues with the REDCap API returning fewer records than expected when given certain combinations of request parameters.
`header_labs`	Logical indicating whether to export column names as labels (`TRUE`) or raw variable names (`FALSE`). Defaults to `FALSE` to return raw variable names.
`checkbox_labs`	Logical indicating whether to export checkbox labels (`TRUE`) or statuses (i.e. "Unchecked" or "Checked") (`FALSE`). Defaults to `FALSE` to export statuses. Note this argument is only relevant when `value_labs` is `TRUE` — if `value_labs` is `FALSE` checkbox variables will always be exported as raw values (usually "0"/"1").
`use_factors`	Logical indicating whether categorical REDCap variables (radio, dropdown, yesno, checkbox) should be returned as factors. Factor levels can either be raw values (e.g. "0"/"1") or labels (e.g. "No"/"Yes") depending on arguments `value_labs` and `checkbox_labs`. Defaults to `FALSE`.
`times_chron`	Logical indicating whether to reclass time variables using chron::times (`TRUE`) or leave as character HH:MM format (`FALSE`). Defaults to `TRUE`. Note this only applies to variables of REDCap type "Time (HH:MM)", and not "Time (MM:SS)".
`date_range_begin`	Fetch only records created or modified after a given date-time. Use format "YYYY-MM-DD HH:MM:SS" (e.g., "2017-01-01 00:00:00" for January 1, 2017 at midnight server time). Defaults to NULL to omit a lower time limit.
`date_range_end`	Fetch only records created or modified before a given date-time. Use format "YYYY-MM-DD HH:MM:SS" (e.g., "2017-01-01 00:00:00" for January 1, 2017 at midnight server time). Defaults to NULL to omit a lower time limit.
`fn_dates`	Function to parse REDCap date variables. Defaults to `parse_date`, an internal wrapper to `lubridate::parse_date_time`. If date variables have been converted to numeric (e.g. by writing to Excel), set to e.g. `lubridate::as_date` to convert back to dates.
`fn_dates_args`	List of arguments to pass to `fn_dates`. Can set to empty list `list()` if using a function that doesn't take any arguments.
`fn_datetimes`	Function to parse REDCap datetime variables. Defaults to `lubridate::parse_date_time`.
`fn_datetimes_args`	List of arguments to pass to `fn_datetimes`. Can set to empty list `list()` if using a function that doesn't take any arguments.
`na`	Character vector of strings to interpret as missing values. Passed to readr::read_csv. Defaults to `c("", "NA")`.
`dag`	Logical indicating whether to export the `redcap_data_access_group` field (if used in the project). Defaults to `TRUE`.
`batch_size`	Number of records to fetch per batch. Defaults to `100L`. Set to `Inf` or `NA` to fetch all records at once.
`batch_delay`	Delay in seconds between fetching successive batches, to give the REDCap server time to respond to other requests. Defaults to `0.5`.
`double_resolve`	Logical indicating whether to resolve double-entries (i.e. records entered in duplicate using REDCap's Double Data Entry module), by filtering to the lowest entry number associated with each unique record. If a project uses double-entry, the record IDs returned by an "Export Records" API request will be a concatenation of the normal record ID and the entry number (1 or 2), normally separated by "–" (e.g. "P0285–1"). To resolve double entries we move the entry number portion of the ID to its own column (`entry`), identify all entries belonging to the same unique record, and retain only the row with the lowest entry number for each unique record. Unique records are identified using the record ID column (after separating the entry number portion), and any of the following columns when present (accounting for argument `header_labs`): redcap_event_name (Redcap Event), redcap_repeat_instrument (Repeat Instrument), redcap_repeat_instance (Repeat Instance).
`double_remove`	Logical indicating whether to remove double-entries (i.e. records entered in duplicate using REDCap's Double Data Entry module), by filtering out records where the record ID field contains pattern `double_sep` (see next argument), so that only merged records remain.
`double_sep`	If `double_resolve` is `TRUE`, the string separator used to split the record ID field into the record ID and entry number. Defaults to "–".

Value

A tibble-style data frame containing the requested records

Removing empty rows

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

fetch_records(conn, forms = "my_form")

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

fetch_records(conn, forms = "my_form")

## End(Not run)

Generate data validation queries for a REDCap project based on branching logic specified in the project codebook

Description

Generates two types of data validation queries using the project codebook (see meta_dictionary) and translate_logic:

Field missing: Branching logic evaluates to TRUE (if specified), but field is missing. By default only applies to required fields (required_field == "y") (can modify with argument non_required).
Field not missing: Branching logic evaluates to FALSE but field is not missing. Applies to any field with branching logic.

Usage

generate_queries(
  conn,
  forms = NULL,
  dict = meta_dictionary(conn, forms = forms, expand_checkbox = FALSE),
  lang = "en",
  query_types = "both",
  non_required = FALSE,
  drop_redundant = FALSE,
  field_nchar_max = 80L,
  on_error = "warn"
)
generate_queries(
  conn,
  forms = NULL,
  dict = meta_dictionary(conn, forms = forms, expand_checkbox = FALSE),
  lang = "en",
  query_types = "both",
  non_required = FALSE,
  drop_redundant = FALSE,
  field_nchar_max = 80L,
  on_error = "warn"
)

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`forms`	Character vector of forms (i.e. instruments) to include. Set to `NULL` (the default) to generate queries for all forms in the project.
`dict`	Metadata dictionary. By default is fetched automatically with `meta_dictionary`, but it's included as an argument here to allow the user to modify the dictionary before passing to `generate_queries` (e.g. to correct bugs in branching logic). If passing a modified version, make sure it is initially fetched with argument `expand_checkbox = FALSE`.
`lang`	Query language, either English ("en") or French ("fr"). Defaults to "en".
`query_types`	Which type of queries to generate (see Description above). Options are "missing", "not missing", or "both". Defaults to "both".
`non_required`	Logical indicating whether to include non-required fields in queries of type "Field missing". Defaults to `FALSE`.
`drop_redundant`	Logical indicating whether to simplify expressions by removing redundant components from expressions that test both for equality and inequality with the same variable. E.g.: `var == "X" & var != ""` becomes `var == "X"`
`field_nchar_max`	Integer indicating the maximum number of characters to allow in field name labels before they are truncated and appended with "...". Defaults to 80L.
`on_error`	What to do if one or more elements of statements can't be translated into valid R expressions? Options are "ignore" (return `NA` for relevant elements), "warn" (return `NA` for relevant elements and give warning), or "fail" (throw error). Defaults to "warn".

Value

A tibble-style data frame specifying queries, with the following 7 columns:

query_id: Unique query identifier based on form name and integer sequence
field_name: Field name (from REDCap dictionary, see meta_dictionary)
form_name: Form name (from REDCap dictionary)
required: Is it a required field in REDCap dictionary ("y" or ⁠<NA>⁠) ?
description: Description of query (e.g. "Missing: [Signed consent forms?]")
suggestion: Suggestion for query resolution. A human-readable translation of query expression (e.g. If [Is the participant 18 years or older?] is "Yes", item [Signed consent forms?] should not be missing)
branching_logic: Branching logic for given field (from REDCap dictionary)
query: R-style query expression (can be evaluated with queryr::query)

Import records into a REDCap project

Description

Import records into a REDCap project

Usage

import_records(
  conn,
  data,
  type = c("flat", "eav"),
  overwrite = "normal",
  return = "count"
)
import_records(
  conn,
  data,
  type = c("flat", "eav"),
  overwrite = "normal",
  return = "count"
)

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`data`	A data.frame containing record data to import into REDCap
`type`	One of: "flat": data in wide-form with one record per row (default) "eav": data in long-form with one row per participant/instance/field (data should have columns "record", "field_name", and "value", and if longitudinal then also "redcap_event_name" and "redcap_repeat_instance")
`overwrite`	Overwrite behaviour. Either "normal" to prevent missing values from overwriting data, or "overwrite" to allow data to be overwritten with missing values. Defaults to "normal".
`return`	What to return. Use "count" to return a count of imported records, "ids" to return a vector of the IDs that were imported, or "nothing" to return nothing. Defaults to "count".

Value

Depends on argument return. Either a count of imported records, a vector of record IDs, or nothing.

Export REDCap project arms

Description

Execute an "Export Arms" API request to fetch the "arms" (number and name) associated with a REDCap project.

Usage

meta_arms(conn)
meta_arms(conn)

Arguments

conn

A REDCap API connection object (created with rconn)

Value

A tibble-style data frame with 2 columns:

arm_num
name

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_arms(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_arms(conn)

## End(Not run)

Fetch variable dictionary for a REDCap project

Description

Execute an "Export Metadata (Data Dictionary)" API request to fetch a tibble-style data frame containing the project codebook (field names, types, labels, choices, validation, etc.).

Usage

meta_dictionary(
  conn,
  forms = NULL,
  expand_checkbox = TRUE,
  add_complete = FALSE,
  cols_omit = c("section_header", "custom_alignment", "question_number",
    "matrix_group_name", "matrix_ranking")
)
meta_dictionary(
  conn,
  forms = NULL,
  expand_checkbox = TRUE,
  add_complete = FALSE,
  cols_omit = c("section_header", "custom_alignment", "question_number",
    "matrix_group_name", "matrix_ranking")
)

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`forms`	Character vector of forms (i.e. instruments) to include in the return. Set to `NULL` (the default) to return dictionary entries for all forms in the project.
`expand_checkbox`	Logical indicating whether to expand checkbox variables. Defaults to `TRUE`. Unlike an "Export Records" API request (see `fetch_records`), which returns 1 column for each checkbox option, an "Export Metadata (Data Dictionary)" request returns a single row for each field — including checkbox fields. Thus, the `field_name` and `field_label` entries for checkbox variables in the data dictionary will never exactly match the respective column names or values returned by `fetch_records`. When `expand_checkbox` is `TRUE`, rows for checkbox fields are expanded to 1 row per checkbox option, so that dictionary entries for `field_name`, `field_label`, and `choices` will always match the relevant entries returned by `fetch_records`.
`add_complete`	Logical indicating whether to add "{form}_complete" fields to the dictionary, one for each form included in the return. These will be of field_type "radio" with possible choices "0, Incomplete \| 1, Unverified \| 2, Complete". Defaults to `FALSE`.
`cols_omit`	Character vector of dictionary columns to omit from the return for brevity. Set to `NULL` to return all columns.

Value

A tibble-style data frame containing the project dictionary. Note that some of the returned column names are shortened versions of the original column names returned by the API:

Original	Returned
`select_choices_or_calculations`	`choices`
`text_validation_type_or_show_slider_number`	`validation`
`text_validation_min`	`validation_min`
`text_validation_max`	`validation_max`

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_dictionary(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_dictionary(conn)

## End(Not run)

Fetch event names and labels for a REDCap project

Description

Execute an "Export Events" API request to fetch a tibble-style data frame containing event names and labels. Note that this request type is not available for 'classic projects', from which event details cannot be exported.

Usage

meta_events(conn, on_error = "fail")
meta_events(conn, on_error = "fail")

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`on_error`	How to handle errors returned by the API (e.g. events cannot be exported for classic projects). Set to "fail" to halt execution and return the API error message, or "null" to ignore the error and return `NULL`. Defaults to "fail".

Value

A tibble-style data frame with 7 columns:

event_name
arm_num
day_offset
offset_min
offset_max
unique_event_name
custom_event_label

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_events(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_events(conn)

## End(Not run)

Fetch field option values and labels for factor-type variables in a REDCap project

Description

Converts field options and labels from the metadata dictionary (see meta_dictionary), which has 1 row per variable and field options in compact string-form, to long form with 1 row per option. E.g.:

Dictionary version (1 row per variable):

`field_name`	`form_name`	`field_type`	`choices`
consented	enrollment	radio	0, No \| 1, Yes

Long format (1 row per option):

`field_name`	`form_name`	`field_type`	`value`	`label`
consented	enrollment	radio	0	No
consented	enrollment	radio	1	Yes

Usage

meta_factors(
  conn,
  forms = NULL,
  expand_checkbox = TRUE,
  add_complete = FALSE,
  types = c("radio", "yesno", "dropdown", "checkbox")
)
meta_factors(
  conn,
  forms = NULL,
  expand_checkbox = TRUE,
  add_complete = FALSE,
  types = c("radio", "yesno", "dropdown", "checkbox")
)

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`forms`	Character vector of forms (i.e. instruments) to include. Set to `NULL` (the default) to return field options for all forms in the project.
`expand_checkbox`	Logical indicating whether to expand checkbox variables. Defaults to `TRUE`. Unlike an "Export Records" API request (see `fetch_records`), which returns 1 column for each checkbox option, an "Export Metadata (Data Dictionary)" request returns a single row for each field — including checkbox fields. Thus, the `field_name` and `field_label` entries for checkbox variables in the data dictionary will never exactly match the respective column names or values returned by `fetch_records`. When `expand_checkbox` is `TRUE`, rows for checkbox fields are expanded to 1 row per checkbox option, so that dictionary entries for `field_name`, `field_label`, and `choices` will always match the relevant entries returned by `fetch_records`.
`add_complete`	Logical indicating whether to add "{form}_complete" fields to the dictionary, one for each form included in the return. These will be of field_type "radio" with possible choices "0, Incomplete \| 1, Unverified \| 2, Complete". Defaults to `FALSE`.
`types`	Character vector of variable types to return field options for. Defaults to `c("radio", "yesno", "dropdown", "checkbox")`.

Value

A tibble-style data frame with 6 columns:

field_name
form_name
field_type
field_label
value
label

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_factors(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_factors(conn)

## End(Not run)

Fetch exported field names for a REDCap project

Description

Execute an "Export List of Export Field Names" API request to fetch a tibble-style data frame containing field (i.e. variable) names as listed in the project codebook (column original_field_name) and the corresponding exported variable name(s) (column export_field_name).

Original and exported field names will be identical except in the case of checkbox-type variables. A given checkbox variable (e.g. "patient_status") will have a single entry in the codebook (i.e. field_name = "patient_status"), but will be exported as multiple variables — one for each possible choice value.

`original_field_name`	`choice_value`	`export_field_name`
patient_status	1	patient_status___1
patient_status	2	patient_status___2
patient_status	3	patient_status___3
patient_status	88	patient_status___88

Usage

meta_fields(conn)
meta_fields(conn)

Arguments

conn

A REDCap API connection object (created with rconn)

Value

A tibble-style data frame with 3 columns:

original_field_name
choice_value
export_field_name

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_fields(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_fields(conn)

## End(Not run)

Fetch instrument names and labels for a REDCap project

Description

Execute an "Export Instrument (Data Entry Forms)" API request to fetch a tibble-style data frame containing instrument names and labels.

Usage

meta_forms(conn)
meta_forms(conn)

Arguments

conn

A REDCap API connection object (created with rconn)

Value

A tibble-style data frame with 2 columns:

instrument_name
instrument_label

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_forms(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_forms(conn)

## End(Not run)

Fetch instrument-event mappings for a REDCap project

Description

Execute an "Export Instrument-Event Mappings" API request to fetch a tibble-style data frame containing the mapping between instruments and events. Note that this request type is not available for 'classic projects', from which event details cannot be exported.

Usage

meta_mapping(conn, on_error = "fail")
meta_mapping(conn, on_error = "fail")

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`on_error`	How to handle errors returned by the API (e.g. events cannot be exported for classic projects). Set to "fail" to halt execution and return the API error message, or "null" to ignore the error and return `NULL`. Defaults to "fail".

Value

A tibble-style data frame with 3 columns:

arm_num
unique_event_name
form

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_mapping(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_mapping(conn)

## End(Not run)

Fetch repeating instrument names and labels for a REDCap project

Description

Execute an "Export Repeating Instruments and Events" API request to fetch a tibble-style data frame containing repeating instrument names and labels.

Usage

meta_repeating(conn, on_error = "fail")
meta_repeating(conn, on_error = "fail")

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`on_error`	How to handle errors returned by the API (e.g. events cannot be exported for classic projects). Set to "fail" to halt execution and return the API error message, or "null" to ignore the error and return `NULL`. Defaults to "fail".

Value

A tibble-style data frame with 2 columns:

instrument_name
instrument_label

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_repeating(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

meta_repeating(conn)

## End(Not run)

Convert a REDCap project log file to a tidy data frame

Description

REDCap project log files have a complicated format where multiple types of information are contained in a single column. For example the column action contains the relevant record ID, the type of action that was taken (e.g. Updated / Created / Deleted), and sometimes further details about the source of the action (e.g. API / Import / Automatic field calculation). The details column contains a string of variable/value combinations describing any changes (e.g. "var1 = '0', var2 = '1', var3(1) = checked"), and may also contain the relevant repeat instance number (e.g. "[instance = 3]").

The parse_logging() function tidies up the log file by splitting the record ID, action, action type, and repeat instance into separate columns. Optionally, the string of variable/value changes in the details column may be further transformed to long format to yield a single row for each combination of variable and value.

Note that this function only deals with log entries of type Created / Deleted / Updated Record. All other log entries (e.g. Data Export, Manage/Design, Edited Role, User Assigned to Role) will be filtered out.

Usage

parse_logging(x, format_long = FALSE, dict = NULL)
parse_logging(x, format_long = FALSE, dict = NULL)

Arguments

`x`	REDCap project log file (data frame), e.g. returned by `project_logging`
`format_long`	Logical indicating whether to transform the log file to long format, with one row per variable-value combination. Defaults to `FALSE`.
`dict`	A REDCap metadata dictionary (data frame), e.g. returned by `meta_dictionary`. Only needed when argument `format_long` is `TRUE`.

Value

A tibble-style data frame with 8 columns:

rowid: Row number based on original log file. There may be gaps for rows that have been excluded from the output because they reflected an action type other than create / delete / update.
timestamp: unchanged from original log file
username: unchanged from original log file
action: One of "Created Record", "Deleted Record", or "Updated Record", extracted from original details column
action_type: Parenthetical details, if any, extracted from original action column (e.g. "(API)", "(import)", "(Auto calculation)")
record_id: Record ID, extracted from original action column
redcap_repeat_instance: Instance number (integer), extracted from original details column. Note that 1st instances are not explicitly specified in the log file and will appear as NA
details: String of variable value pairs (e.g. "var1 = '0', var2 = '1', var3(1) = checked"), reflecting the data that was modified

If argument format_long is TRUE the details column will be replaced with three other columns:

form_name: Form name, joined from metadata dictionary based on variable field_name. Will be ⁠<NA>⁠ in cases where field name has been changed or removed and therefore doesn't appear in the dictionary, or for fields not associated with a specific form like redcap_data_access_group.
field_name: Field name, extracted from original details column
value: Value, extracted from original details column

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

parse_logging(project_logging(conn))

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

parse_logging(project_logging(conn))

## End(Not run)

Convert a REDCap project XML file to a tidy data frame of project records

Description

Extract records from a REDCap project XML file (e.g. returned by project_xml) and assemble into a tidy long-form data frame, with one row for each combination of record x field x event x instance.

Usage

parse_xml(x)
parse_xml(x)

Arguments

`x`	A REDCap project XML obect of class `xml_document`, e.g. returned by `project_xml`

Value

A tibble-style data frame with 6 columns:

record_id
form
redcap_event
redcap_repeat_instance
field
value

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

parse_xml(project_xml(conn))

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

parse_xml(project_xml(conn))

## End(Not run)

Export REDCap user information

Description

Execute an "Export Data Access Groups (DAGs)" API request to fetch the DAGs (labels and code names) associated with a REDCap project.

Usage

project_dags(conn)
project_dags(conn)

Arguments

conn

A REDCap API connection object (created with rconn)

Value

A tibble-style data frame with 2 columns:

data_access_group_name
unique_group_name

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_dags(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_dags(conn)

## End(Not run)

Export REDCap Project information

Description

Execute an "Export Project Info" API request to fetch project-related details (e.g. title, creation time, production status, language, etc.) corresponding to a REDCap project.

Usage

project_info(conn)
project_info(conn)

Arguments

conn

A REDCap API connection object (created with rconn)

Value

A tibble-style data frame containing the columns returned by an "Export Project Info" API request

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_info(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_info(conn)

## End(Not run)

Export project logging (audit trail) for a REDCap project

Description

Execute an "Export Logging" API request to export the logging (audit trail) of all changes made to the project, including data exports, data changes, project metadata changes, modification of user rights, etc.

Usage

project_logging(
  conn,
  type = NULL,
  user = NULL,
  record = NULL,
  time_start = NULL,
  time_end = NULL,
  timestamp_to_posix = TRUE
)
project_logging(
  conn,
  type = NULL,
  user = NULL,
  record = NULL,
  time_start = NULL,
  time_end = NULL,
  timestamp_to_posix = TRUE
)

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`type`	Type of logging to return. Defaults to NULL to return all types. Specific logging types include: "export": Data export "manage": Manage/Design "user": User or role created-updated-deleted "record": Record created-updated-deleted "record_add": Record created (only) "record_edit": Record updated (only) "record_delete": Record deleted (only) "lock_record": Record locking & e-signatures "page_view": Page Views
`user`	REDCap username to fetch logs for. Defaults to NULL to fetch logs relating to all users. Note that, in the current API version (10.8.5), it's not possible to pass a character vector with multiple usernames (i.e. one user per request, or NULL for all).
`record`	Record ID to fetch logs for. Defaults to NULL to fetch logs relating to all record IDs. Note that, in the current API version (10.8.5), it's not possible to pass a character vector with multiple record IDs (i.e. one record per request, or NULL for all).
`time_start`	Fetch logs from after a given date-time. Use format "YYYY-MM-DD HH:MM". Defaults to NULL to omit a lower time limit.
`time_end`	Fetch logs from before a given date-time. Use format "YYYY-MM-DD HH:MM". Defaults to NULL to omit an upper time limit.
`timestamp_to_posix`	Logical indicating whether to convert the `timestamp` column to class POSIXct using `lubridate::as_datetime`. Defaults to TRUE.

Value

A tibble-style data frame with 4 columns:

timestamp
username
actions
details

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_logging(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_logging(conn)

## End(Not run)

Export REDCap user information

Description

Execute an "Export Users" API request to fetch user-related details (e.g. username, email, access permissions, etc.) corresponding to a REDCap project.

Usage

project_users(conn)
project_users(conn)

Arguments

conn

A REDCap API connection object (created with rconn)

Value

A tibble-style data frame containing the columns returned by an "Export Users" API request

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_users(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_users(conn)

## End(Not run)

Export REDCap mapping between users and Data Access Groups (DAGs)

Description

Execute an "Export User-DAG Assignments" API request to fetch the mapping between users and Data Access Groups (DAGs) associated with a REDCap project.

Usage

project_users_dags(conn)
project_users_dags(conn)

Arguments

conn

A REDCap API connection object (created with rconn)

Value

A tibble-style data frame with 2 columns:

username
redcap_data_access_group

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_users_dags(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_users_dags(conn)

## End(Not run)

Export REDCap Project XML file

Description

Execute an "Export Entire Project as REDCap XML File" API request to fetch all metadata (and optionally also data records) corresponding to a REDCap project.

Usage

project_xml(
  conn,
  meta_only = FALSE,
  records = NULL,
  fields = NULL,
  events = NULL,
  filter_logic = NULL,
  export_dag = FALSE,
  export_survey = FALSE,
  export_files = FALSE
)
project_xml(
  conn,
  meta_only = FALSE,
  records = NULL,
  fields = NULL,
  events = NULL,
  filter_logic = NULL,
  export_dag = FALSE,
  export_survey = FALSE,
  export_files = FALSE
)

Arguments

`conn`	A REDCap API connection object (created with `rconn`)
`meta_only`	Logical indicating whether to fetch only the project metadata (if `TRUE`) or both the metadata and data records (if `FALSE`). Defaults to `FALSE` to fetch both metadata and data.
`records`	Optional character vector of specific record IDs to fetch record data for. Only used when `meta_only = FALSE`.
`fields`	Optional character vector of specific fields to fetch record data for. Only used when `meta_only = FALSE`.
`events`	Optional character vector of specific events to fetch record data for. Only used when `meta_only = FALSE`.
`filter_logic`	Optional character string containing a REDCap-style expression used to filter records returned by the API (e.g. "[age] > 30")
`export_dag`	Logical indicating whether to export the redcap_data_access_group field. Defaults to `FALSE`.
`export_survey`	Logical indicating whether to export survey identifier or timestamp fields, if surveys are used in the project. Defaults to `FALSE`.
`export_files`	Logical indicating whether to export uploaded files. Note this may lead to large exports. Defaults to `FALSE`.

Value

An object of class xml_document

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_xml(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

project_xml(conn)

## End(Not run)

Connection to a REDCap Database

Description

Creates an object of class "rconn" containing the URL and token used to access a REDCap project API.

Usage

rconn(url, token, config = httr::config())
rconn(url, token, config = httr::config())

Arguments

`url`	URL for a REDCap database API
`token`	REDCap project API token (good practice to set using an environmental variable, e.g. with `Sys.getenv`).
`config`	Optional configuration settings passed to `httr::POST`. Defaults to `httr::config()`.

Value

An object of class "rconn", to be passed as the first argument to most other redcap functions.

Examples

conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

Reclass columns of a data frame to match classes specified in a metadata dictionary

Description

Reclass columns of a data frame to match classes specified in a metadata dictionary

Usage

reclass(
  x,
  dict,
  use_factors = FALSE,
  value_labs = TRUE,
  header_labs = FALSE,
  times_chron = TRUE,
  fn_dates = parse_date,
  fn_dates_args = list(orders = c("Ymd", "dmY")),
  fn_datetimes = lubridate::parse_date_time,
  fn_datetimes_args = list(orders = c("Ymd HMS", "Ymd HM"))
)
reclass(
  x,
  dict,
  use_factors = FALSE,
  value_labs = TRUE,
  header_labs = FALSE,
  times_chron = TRUE,
  fn_dates = parse_date,
  fn_dates_args = list(orders = c("Ymd", "dmY")),
  fn_datetimes = lubridate::parse_date_time,
  fn_datetimes_args = list(orders = c("Ymd HMS", "Ymd HM"))
)

Arguments

`x`	A data frame representing a REDCap form
`dict`	A metadata dictionary
`use_factors`	Logical indicating whether categorical REDCap variables (radio, dropdown, yesno, checkbox) should be returned as factors. Factor levels can either be raw values (e.g. "0"/"1") or labels (e.g. "No"/"Yes") depending on arguments `value_labs` and `checkbox_labs`. Defaults to `FALSE`.
`value_labs`	Logical indicating whether to return value labels (`TRUE`) or raw values (`FALSE`) for categorical REDCap variables (radio, dropdown, yesno, checkbox). Defaults to `TRUE` to return labels.
`header_labs`	Logical indicating whether to export column names as labels (`TRUE`) or raw variable names (`FALSE`). Defaults to `FALSE` to return raw variable names.
`times_chron`	Logical indicating whether to reclass time variables using chron::times (`TRUE`) or leave as character HH:MM format (`FALSE`). Defaults to `TRUE`. Note this only applies to variables of REDCap type "Time (HH:MM)", and not "Time (MM:SS)".
`fn_dates`	Function to parse REDCap date variables. Defaults to `parse_date`, an internal wrapper to `lubridate::parse_date_time`. If date variables have been converted to numeric (e.g. by writing to Excel), set to e.g. `lubridate::as_date` to convert back to dates.
`fn_dates_args`	List of arguments to pass to `fn_dates`. Can set to empty list `list()` if using a function that doesn't take any arguments.
`fn_datetimes`	Function to parse REDCap datetime variables. Defaults to `lubridate::parse_date_time`.
`fn_datetimes_args`	List of arguments to pass to `fn_datetimes`. Can set to empty list `list()` if using a function that doesn't take any arguments.

Convert between values and labels for factor-type variables (e.g. yes/no, radio, dropdown, checkbox)

Description

Convert between values and labels for factor-type variables (e.g. yes/no, radio, dropdown, checkbox)

Usage

recode_labels(
  x,
  conn,
  dict = redcap::meta_dictionary(conn, add_complete = TRUE),
  convert_to = c("labels", "values"),
  types = c("radio", "yesno", "dropdown", "checkbox"),
  header_labs = FALSE
)
recode_labels(
  x,
  conn,
  dict = redcap::meta_dictionary(conn, add_complete = TRUE),
  convert_to = c("labels", "values"),
  types = c("radio", "yesno", "dropdown", "checkbox"),
  header_labs = FALSE
)

Arguments

`x`	Data frame representing a REDCap form (e.g. from a previous export using `fetch_records`)
`conn`	A REDCap API connection object (created with `rconn`)
`dict`	REDCap metadata dictionary. Defaults to fetching the current version with `meta_dictionary`
`convert_to`	Convert values to labels ("labels") or labels to values ("values")
`types`	Types of REDCap variables to convert, based on column "field_type" in the metadata dictionary. Defaults to `c("radio", "yesno", "dropdown", "checkbox")`.
`header_labs`	Logical indicating whether column names of `x` are labels (TRUE) or raw variable names (FALSE). Default assumes header has raw variable names (i.e. FALSE).

Fetch the REDCap database version used for a particular project

Description

Execute an "Export REDCap version" API request

Usage

redcap_version(conn)
redcap_version(conn)

Arguments

conn

A REDCap API connection object (created with rconn)

Value

A character string

Examples

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

redcap_version(conn)

## End(Not run)

## Not run: 
conn <- rconn(
  url = "https://redcap.msf.fr/api/",
  token = Sys.getenv("MY_REDCAP_TOKEN")
)

redcap_version(conn)

## End(Not run)

Translate REDCap branching logic into R expressions

Description

Translate REDCap branching logic into expressions evaluable in R. E.g.

Translation step	Example expression
0. Initial REDCap logic	`⁠[over_18]='1' and [signed_consent]<>''⁠`
1. Translate to R	`over_18 == '1' & signed_consent != ''`
2. (Optional) Swap values/labels	`over_18 == 'Yes' & signed_consent != ''`
3. (Optional) Use is.na	`over_18 == 'Yes' & !is.na(signed_consent)`
4. (Optional) Use %in%	`over_18 %in% 'Yes' & !is.na(signed_consent)`

Usage

translate_logic(
  x,
  use_value_labs = TRUE,
  use_header_labs = FALSE,
  use_is_na = TRUE,
  use_in = TRUE,
  drop_redundant = FALSE,
  field_nchar_max = 80L,
  meta_factors = NULL,
  meta_dictionary = NULL,
  on_error = "warn"
)
translate_logic(
  x,
  use_value_labs = TRUE,
  use_header_labs = FALSE,
  use_is_na = TRUE,
  use_in = TRUE,
  drop_redundant = FALSE,
  field_nchar_max = 80L,
  meta_factors = NULL,
  meta_dictionary = NULL,
  on_error = "warn"
)

Arguments

`x`	A character vector of REDCap branching logic statements
`use_value_labs`	Logical indicating whether to replace factor option values with labels (based on the mapping defined in `meta_factors`). E.g.: `y == '1'` becomes `y == 'Yes'`
`use_header_labs`	Logical indicating whether to use labels instead of variable names as column names (based on the mapping defined in `meta_dictionary`). E.g.: `age >= 18` becomes `"Participant's age" >= 18`
`use_is_na`	Logical indicating whether to replace REDCap-style tests for missingness with `is.na`. E.g.: `y == ""` becomes `is.na(y)` `y != ""` becomes `!is.na(y)`
`use_in`	Logical indicating whether to replace instances of `==` and `!=` associated with factor-type variables (as defined in `meta_factors`) with `%in%`. E.g.: `y == 'Yes'` becomes `y %in% 'Yes'` `y != 'Yes'` becomes `!y %in% 'Yes'`
`drop_redundant`	Logical indicating whether to simplify expressions by removing redundant components from expressions that test both for equality and inequality with the same variable. E.g.: `var == "X" & var != ""` becomes `var == "X"`
`field_nchar_max`	Integer indicating the maximum number of characters to allow in field name labels before they are truncated and appended with "...". Defaults to 80L.
`meta_factors`	A data frame containing variable names (column `field_name`) and corresponding values (column `value`) and labels (column `label`) for factor-type variables. Fetch with `meta_factors`. Only needed if either `use_value_labs` or `use_in` are `TRUE`.
`meta_dictionary`	A data frame containing variable names (column `field_name`) and labels (column `field_label`). Fetch with `meta_dictionary`. Only needed if `use_header_labs` is `TRUE`.
`on_error`	What to do if one or more elements of statements can't be translated into valid R expressions? Options are "ignore" (return `NA` for relevant elements), "warn" (return `NA` for relevant elements and give warning), or "fail" (throw error). Defaults to "warn".

Value

A character vector of R-style expressions

Examples

# normally would fetch factor metadata with redcap::meta_factors(), but here
# we'll create a simple example by hand
df_factors <- data.frame(
  field_name = c("head_household", "head_household"),
  value = c("0", "1"),
  label = c("No", "Yes"),
  stringsAsFactors = FALSE
)

redcap_logic <- "head_household=1 and age<>\"\""
translate_logic(redcap_logic, meta_factors = df_factors)

# normally would fetch factor metadata with redcap::meta_factors(), but here
# we'll create a simple example by hand
df_factors <- data.frame(
  field_name = c("head_household", "head_household"),
  value = c("0", "1"),
  label = c("No", "Yes"),
  stringsAsFactors = FALSE
)

redcap_logic <- "head_household=1 and age<>\"\""
translate_logic(redcap_logic, meta_factors = df_factors)

Package 'redcap'

Help Index

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Description

Usage

Arguments

Value

Examples

Fetch records from multiple REDCap forms, returning separate list elements for each form

Description

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Removing empty rows

Examples

Fetch records for a REDCap project

Description

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Examples

Generate data validation queries for a REDCap project based on branching logic specified in the project codebook

Description

Usage

Arguments

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Description

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Arguments

Value

Export REDCap project arms

Description

Usage

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Value

Examples

Fetch variable dictionary for a REDCap project

Description

Usage

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Examples

Fetch event names and labels for a REDCap project

Description

Usage

Arguments

Value

Examples

Fetch field option values and labels for factor-type variables in a REDCap project

Description

Usage

Arguments

Value

See Also

Examples

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Description

Usage

Arguments

Value

Examples

Fetch instrument names and labels for a REDCap project

Description

Usage

Arguments

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Examples

Fetch instrument-event mappings for a REDCap project

Description

Usage

Arguments

Value

Examples

Fetch repeating instrument names and labels for a REDCap project

Description

Usage

Arguments

Value