Package 'tidyREDCap'

Drop the label from a variable

Description

There is a reported issues with joins on data (without a reprex) that seem to be caused by the labels. As a possible solution this can be used to drop labels.

Usage

drop_label(df, x)

Arguments

df	the name of the data frame
x	the quoted name of the variable

Value

df

---

Drop all the labels from a variable

Description

There is an issue with the function we are using to add column labels. If you run into problems processing the labels.

Usage

drop_labels(df)

Arguments

df	The data frame with column labels that you want to drop

Value

df without column labels

Examples

## Not run: 
demographics |>
  drop_labels() |>
  skimr::skim()

## End(Not run)

---

Import all instruments into individual R tables

Description

This function takes the url and key for a REDCap project and returns a table for each instrument/form in the project.

Usage

import_instruments(
  url,
  token,
  drop_blank = TRUE,
  record_id = "record_id",
  first_record_id = 1,
  envir = .GlobalEnv
)

Arguments

url	The API URL for your the instance of REDCap
token	The API security token
drop_blank	Drop records that have no data. TRUE by default.
record_id	Name of record_id variable (if it was changed in REDCap).
first_record_id	A value of the custom record_id variable (if changed in REDCap). To improve the speed of the import, tidyREDCap pulls in a single record twice. By default if uses the first record. If you have a custom record_id variable and if its the first record identifier is not 1, specify a record identifier value here. For example if you are using dude_id instead of record_id and dude_id has a value of "first dude" for one of its records this argument would be first_record_id = "first dude".
envir	The name of the environment where the tables should be saved.

Value

one data.frame for each instrument/form in a REDCap project. By default the datasets are saved into the global environment.

Examples

## Not run: 
import_instruments(
  "https://redcap.miami.edu/api/",
  Sys.getenv("test_API_key")
)

## End(Not run)

---

Convert a "choose all that apply" Question Into a Binary Word

Description

This function takes a data frame holding binary variables with values corresponding to a dummy-coded "choose all that apply" question. It can be used for any binary word problem.

Usage

make_binary_word(df, yes_value = "Checked", the_labels = letters)

Arguments

df	A data frame with the variables corresponding to binary indicators (the dummy coded variables) for a "choose all that apply" question.
yes_value	A character string that corresponds to choosing "yes" in the binary variables of df. Defaults to the REDCap "Checked" option.
the_labels	A character vector of single letters holding the letters used to make the binary word. See the article/vignette called "Make Binary Word" for an example: https://raymondbalise.github.io/tidyREDCap/articles/makeBinaryWord.html.

Value

A character vector with length equal to the rows of df, including one letter or underscore for each column of df. For instance, if df has one column for each of the eight options of the Nacho Craving Index example instrument (https://libguides.du.edu/c.php?g=948419&p=6839916), with a row containing the values "Chips" (checked), "Yellow cheese" (unchecked), "Orange cheese" (checked), "White cheese" (checked), "Meat" (checked), "Beans" (unchecked), "Tomatoes" (unchecked) and "Peppers" (checked), then the character string corresponding to that row will be "a_cde__h". The underscores represent that the options for "Yellow cheese", "Beans", and "Tomatoes" were left unchecked.

Examples

test_df <- tibble::tibble(
  q1 = c("Unchecked", "Checked"),
  q2 = c("Unchecked", "Unchecked"),
  q3 = c("Checked", "Checked"),
  q4 = c("Checked", "Unchecked")
)
make_binary_word(test_df)

---

Count The Responses to a Choose All That Apply Question

Description

This will tally the number of responses on a choose all that apply question. This function extracts the option name from the variable labels. So the data set needs to be labeled. See the Make a 'Choose All' Table vignette for help.

Usage

make_choose_all_table(df, variable)

Arguments

df	The name of the data set (it needs labels)
variable	The name of the REDCap variable

Value

A variable's response label without the choose all the question

---

Make a frequency table for a categorical variable

Description

Pass this function either 1) a labeled factor or 2) a data frame and also a factor in the frame, and it will return a janitor-style table. Use subset = TRUE if you are making a report on a variable that is part of a choose all that apply question.

Usage

make_choose_one_table(arg1, arg2, subset = FALSE)

Arguments

arg1	data frame that has a factor or a factor name
arg2	if arg1 is a data frame, this is a factor name
subset	can be equal to TRUE/FALSE. This option removes extra variable name text from the label. This option is useful for choose all that apply questions.

Value

a table

---

Extract an Instrument from an REDCap Export

Description

This function takes a data frame and the names of the first and last variables in an instrumnt and returns a data frame with the instrument.

Usage

make_instrument(
  df,
  first_var,
  last_var,
  drop_which_when = FALSE,
  record_id = "record_id"
)

Arguments

df	A data frame with the instrument
first_var	The name of the first variable in an instrument
last_var	The name of the last variable in an instrument
drop_which_when	Drop the record_id and redcap_event_name variables
record_id	Name of record_id variable (if it was changed in REDCap)

Value

A data frame that has an instrument (with at least one not NA value)

---

Extract an Instrument from an REDCap Export without specifying Variables

Description

This function takes a data frame holding REDCap data, checks if it is a longitudinal study, and returns records that have values.

Usage

make_instrument_auto(df, drop_which_when = FALSE, record_id = "record_id")

Arguments

df	A data frame with the instrument
drop_which_when	Drop the record_id and redcap_event_name variables
record_id	Name of record_id variable (if it was changed in REDCap)

Value

A data frame that has an instrument (with at least one not NA value).

---

make_yes_no

Description

Convert a "Yes-No", "True-False" or "Checkboxes (Multiple Answers)" question in REDCap to a factor holding "Yes" or "No or Unknown". Technically "yes" or "checked" (ignoring case), 1 or TRUE responses are converted to "Yes" and all other values to "No or Unknown". Also see make_yes_no_unknown().

Usage

make_yes_no(x)

Arguments

x	x variable to be converted to hold "Yes" or "No or Unknown"

Value

a factor with "Yes" or "No or Unknown"

Examples

make_yes_no(c(0, 1, NA))
make_yes_no(c("unchecked", "Checked", NA))

---

make_yes_no_unknown

Description

Convert a "Yes-No", "True-False" or "Checkboxes (Multiple Answers)" question in REDCap to a factor holding "No" or "Yes" or "Unknown". Technically "yes" or "checked" (ignoring case), 1 or TRUE responses are converted to "Yes". "No" or "unchecked" (ignoring case), 0 or FALSE are converted to "No". All other values are set to "Unknown". Also see make_yes_no().

Usage

make_yes_no_unknown(x)

Arguments

x	variable to be converted to hold "No", "Yes", or Unknown"

Value

a factor with "No", "Yes", or Unknown"

Examples

make_yes_no_unknown(c(0, 1, NA))
make_yes_no_unknown(c("unchecked", "Checked", NA))

---