Suggests a col_type for each field in a REDCap project
Source:R/redcap-metadata-coltypes.R
redcap_metadata_coltypes.RdThis function inspects a REDCap project to
determine a readr::cols() object that is compatible with the
the project's current definition. It can be copied and pasted into the
R code so future calls to the server will produce a tibble::tibble()
with an equivalent set of data types.
Usage
redcap_metadata_coltypes(
redcap_uri,
token,
print_col_types_to_console = TRUE,
http_response_encoding = "UTF-8",
locale = readr::default_locale(),
verbose = FALSE,
config_options = NULL,
handle_httr = NULL
)Arguments
- redcap_uri
The uri/url of the REDCap server typically formatted as "https://server.org/apps/redcap/api/". Required.
- token
The user-specific string that serves as the password for a project. Required.
- print_col_types_to_console
Should the
readr::cols()object be printed to the console?- http_response_encoding
The encoding value passed to
httr::content(). Defaults to 'UTF-8'.- locale
a
readr::locale()object to specify preferences like number, date, and time formats. This object is passed toreadr::read_csv(). Defaults toreadr::default_locale().- verbose
A boolean value indicating if
messages should be printed to the R console during the operation. The verbose output might contain sensitive information (e.g. PHI), so turn this off if the output might be visible somewhere public. Optional.- config_options
A list of options passed to
httr::POST(). See details athttr::httr_options(). Optional.- handle_httr
The value passed to the
handleparameter ofhttr::POST(). This is useful for only unconventional authentication approaches. It should beNULLfor most institutions. Optional.
Value
A readr::cols() object is returned, which can be
passed to redcap_read() or redcap_read_oneshot().
Additionally objected is printed to the console, see the Details below.
Details
redcap_metadata_coltypes() returns a readr::cols() object in two ways.
First, a literal object is returned that can be passed to
redcap_read() or redcap_read_oneshot().
Second, the function acts as a code generator. It prints text to the console so that it can be copied and pasted into an R file. This is useful to (a) document what fields and data types are expected, and (b) adjust those fields and data types if the defaults can be customized for your needs. For instance, you may choose to exclude some variables or tweak a data type (e.g., changing a patient's height from an integer to a double).
When printing to the console, each data type decision is accompanied by an explanation on the far right. See the output from the examples below. Please file an issue if you think something is too restrictive or can be improved.
The overall heuristic is assign a data type down a waterfall of decisions:
Is the field built into REDCap? This includes an autonumber
record_id,redcap_event_name,redcap_repeat_instrument,redcap_repeat_instance, and an instrument's completion status.What is the field's type? For example, sliders should be an integer, while check marks should be logical(https://stat.ethz.ch/R-manual/R-devel/library/base/html/logical.html.
If the field type is "text", what is the validation type? For instance, a postal code should be a character (even though it looks like a number), a "mdy" should be cast to a date, and a "number_2dp" should be cast to a floating point
If the field type or validation type is not recognized, the field will be cast to character. This will happen when REDCap develops & releases a new type. If you see something like, "# validation doesn't have an associated col_type. Tell us in a new REDCapR issue", please make sure REDCapR is running the newest GitHub release and file a new issue if it's still not recognized.
For details of the current implementation, the decision logic starts about half-way down in the function's source code
*Validation does NOT Guarantee Conformity
If you're coming to REDCap from a database world, this will be unexpected. A validation type does NOT guarantee that all retrieved values will conform to complementary the data type. The validation setting affects only the values entered after the validation was set.
For example, if values like "abcd" where entered in a field for a few months, then the project manager selected the "integer" validation option, all those "abcd" values remain untouched.
This is one reason redcap_metadata_coltypes() prints it suggestions to the console.
It allows the developer to adjust the specifications to match the values
returned by the API. The the "abcd" scenario, consider (a) changing the type
from col_integer to col_character, (b) excluding the trash values,
then (c) in a dplyr::mutate() statement,
use readr::parse_integer() to cast it to the desired type.
References
The official documentation can be found on the 'API Help Page' and 'API Examples' pages on the REDCap wiki (i.e., https://community.projectredcap.org/articles/456/api-documentation.html and https://community.projectredcap.org/articles/462/api-examples.html). If you do not have an account for the wiki, please ask your campus REDCap administrator to send you the static material.
Examples
# \dontrun{
uri <- "https://redcap-dev-2.ouhsc.edu/redcap/api/"
# A simple project
token <- "9A068C425B1341D69E83064A2D273A70" # simple
col_types <- redcap_metadata_coltypes(uri, token)
#> # col_types <- readr::cols_only( # Use `readr::cols_only()` to restrict the retrieval to only these columns
#> col_types <- readr::cols( # Use `readr::cols()` to include unspecified columns
#> # [field] [readr col_type] [explanation for col_type]
#> record_id = readr::col_character() , # DAGs are enabled for the project
#> name_first = readr::col_character() , # field_type is text and validation isn't set
#> name_last = readr::col_character() , # field_type is text and validation isn't set
#> address = readr::col_character() , # field_type is note
#> telephone = readr::col_character() , # validation is 'phone'
#> email = readr::col_character() , # validation is 'email'
#> dob = readr::col_date() , # validation is 'date_ymd'
#> age = readr::col_character() , # field_type is text and validation isn't set
#> sex = readr::col_character() , # field_type is radio
#> demographics_complete = readr::col_integer() , # completion status of form/instrument
#> height = readr::col_double() , # validation is 'number'
#> weight = readr::col_integer() , # validation is 'integer'
#> bmi = readr::col_character() , # field_type is calc
#> comments = readr::col_character() , # field_type is note
#> mugshot = readr::col_character() , # field_type is file
#> health_complete = readr::col_integer() , # completion status of form/instrument
#> race___1 = readr::col_logical() , # field_type is checkbox
#> race___2 = readr::col_logical() , # field_type is checkbox
#> race___3 = readr::col_logical() , # field_type is checkbox
#> race___4 = readr::col_logical() , # field_type is checkbox
#> race___5 = readr::col_logical() , # field_type is checkbox
#> race___6 = readr::col_logical() , # field_type is checkbox
#> ethnicity = readr::col_character() , # field_type is radio
#> interpreter_needed = readr::col_logical() , # field_type is truefalse
#> race_and_ethnicity_complete = readr::col_integer() , # completion status of form/instrument
#> )
redcap_read_oneshot(uri, token, col_types = col_types)$data
#> 5 records and 25 columns were read from REDCap in 0.2 seconds. The http status code was 200.
#> # A tibble: 5 × 25
#> record_id name_first name_last address telephone email dob age sex
#> <chr> <chr> <chr> <chr> <chr> <chr> <date> <chr> <chr>
#> 1 1 Nutmeg Nutmouse "14 Ros… (405) 32… nutt… 2003-08-30 11 0
#> 2 2 Tumtum Nutmouse "14 Ros… (405) 32… tumm… 2003-03-10 11 1
#> 3 3 Marcus Wood "243 Hi… (405) 32… mw@m… 1934-04-09 80 1
#> 4 4 Trudy DAG "342 El… (405) 32… pero… 1952-11-02 61 0
#> 5 5 John Lee Walker "Hotel … (405) 32… left… 1955-04-15 59 1
#> # ℹ 16 more variables: demographics_complete <int>, height <dbl>, weight <int>,
#> # bmi <chr>, comments <chr>, mugshot <chr>, health_complete <int>,
#> # race___1 <lgl>, race___2 <lgl>, race___3 <lgl>, race___4 <lgl>,
#> # race___5 <lgl>, race___6 <lgl>, ethnicity <chr>, interpreter_needed <lgl>,
#> # race_and_ethnicity_complete <int>
# A longitudinal project
token <- "DA6F2BB23146BD5A7EA3408C1A44A556" # longitudinal
col_types <- redcap_metadata_coltypes(uri, token)
#> # col_types <- readr::cols_only( # Use `readr::cols_only()` to restrict the retrieval to only these columns
#> col_types <- readr::cols( # Use `readr::cols()` to include unspecified columns
#> # [field] [readr col_type] [explanation for col_type]
#> study_id = readr::col_character() , # field_type is text and validation isn't set
#> redcap_event_name = readr::col_character() , # longitudinal event_name
#> date_enrolled = readr::col_date() , # validation is 'date_ymd'
#> patient_document = readr::col_character() , # field_type is file
#> first_name = readr::col_character() , # field_type is text and validation isn't set
#> last_name = readr::col_character() , # field_type is text and validation isn't set
#> telephone_1 = readr::col_character() , # validation is 'phone'
#> email = readr::col_character() , # validation is 'email'
#> dob = readr::col_date() , # validation is 'date_ymd'
#> age = readr::col_character() , # field_type is text and validation isn't set
#> ethnicity = readr::col_character() , # field_type is radio
#> race = readr::col_character() , # field_type is dropdown
#> sex = readr::col_character() , # field_type is radio
#> given_birth = readr::col_logical() , # field_type is yesno
#> num_children = readr::col_integer() , # validation is 'integer'
#> gym___0 = readr::col_logical() , # field_type is checkbox
#> gym___1 = readr::col_logical() , # field_type is checkbox
#> gym___2 = readr::col_logical() , # field_type is checkbox
#> gym___3 = readr::col_logical() , # field_type is checkbox
#> gym___4 = readr::col_logical() , # field_type is checkbox
#> aerobics___0 = readr::col_logical() , # field_type is checkbox
#> aerobics___1 = readr::col_logical() , # field_type is checkbox
#> aerobics___2 = readr::col_logical() , # field_type is checkbox
#> aerobics___3 = readr::col_logical() , # field_type is checkbox
#> aerobics___4 = readr::col_logical() , # field_type is checkbox
#> eat___0 = readr::col_logical() , # field_type is checkbox
#> eat___1 = readr::col_logical() , # field_type is checkbox
#> eat___2 = readr::col_logical() , # field_type is checkbox
#> eat___3 = readr::col_logical() , # field_type is checkbox
#> eat___4 = readr::col_logical() , # field_type is checkbox
#> drink___0 = readr::col_logical() , # field_type is checkbox
#> drink___1 = readr::col_logical() , # field_type is checkbox
#> drink___2 = readr::col_logical() , # field_type is checkbox
#> drink___3 = readr::col_logical() , # field_type is checkbox
#> drink___4 = readr::col_logical() , # field_type is checkbox
#> specify_mood = readr::col_integer() , # field_type is slider
#> meds___1 = readr::col_logical() , # field_type is checkbox
#> meds___2 = readr::col_logical() , # field_type is checkbox
#> meds___3 = readr::col_logical() , # field_type is checkbox
#> meds___4 = readr::col_logical() , # field_type is checkbox
#> meds___5 = readr::col_logical() , # field_type is checkbox
#> height = readr::col_double() , # validation is 'number'
#> weight = readr::col_integer() , # validation is 'integer'
#> bmi = readr::col_character() , # field_type is calc
#> comments = readr::col_character() , # field_type is note
#> demographics_complete = readr::col_integer() , # completion status of form/instrument
#> ec_phone = readr::col_character() , # validation is 'phone'
#> ec_confirmed = readr::col_character() , # field_type is radio
#> next_of_kin_contact_name = readr::col_character() , # field_type is text and validation isn't set
#> next_of_kin_contact_address = readr::col_character() , # field_type is note
#> next_of_kin_contact_phone = readr::col_character() , # validation is 'phone'
#> next_of_kin_confirmed = readr::col_character() , # field_type is radio
#> contact_info_complete = readr::col_integer() , # completion status of form/instrument
#> height2 = readr::col_double() , # validation is 'number'
#> weight2 = readr::col_integer() , # validation is 'integer'
#> bmi2 = readr::col_character() , # field_type is calc
#> prealb_b = readr::col_double() , # validation is 'number'
#> creat_b = readr::col_double() , # validation is 'number'
#> npcr_b = readr::col_double() , # validation is 'number'
#> chol_b = readr::col_double() , # validation is 'number'
#> transferrin_b = readr::col_double() , # validation is 'number'
#> baseline_data_complete = readr::col_integer() , # completion status of form/instrument
#> vld1 = readr::col_double() , # validation is 'number'
#> vld2 = readr::col_double() , # validation is 'number'
#> vld3 = readr::col_double() , # validation is 'number'
#> vld4 = readr::col_double() , # validation is 'number'
#> vld5 = readr::col_double() , # validation is 'number'
#> visit_lab_data_complete = readr::col_integer() , # completion status of form/instrument
#> pmq1 = readr::col_character() , # field_type is dropdown
#> pmq2 = readr::col_character() , # field_type is dropdown
#> pmq3 = readr::col_character() , # field_type is radio
#> pmq4 = readr::col_character() , # field_type is dropdown
#> patient_morale_questionnaire_complete = readr::col_integer() , # completion status of form/instrument
#> vbw1 = readr::col_double() , # validation is 'number'
#> vbw2 = readr::col_double() , # validation is 'number'
#> vbw3 = readr::col_double() , # validation is 'number'
#> vbw4 = readr::col_double() , # validation is 'number'
#> vbw5 = readr::col_double() , # validation is 'number'
#> vbw6 = readr::col_character() , # field_type is radio
#> vbw7 = readr::col_character() , # field_type is radio
#> vbw8 = readr::col_character() , # field_type is dropdown
#> vbw9 = readr::col_character() , # field_type is dropdown
#> visit_blood_workup_complete = readr::col_integer() , # completion status of form/instrument
#> vob1 = readr::col_character() , # field_type is radio
#> vob2 = readr::col_character() , # field_type is radio
#> vob3 = readr::col_character() , # field_type is radio
#> vob4 = readr::col_character() , # field_type is radio
#> vob5 = readr::col_character() , # field_type is radio
#> vob6 = readr::col_character() , # field_type is radio
#> vob7 = readr::col_character() , # field_type is note
#> vob8 = readr::col_character() , # field_type is radio
#> vob9 = readr::col_character() , # field_type is radio
#> vob10 = readr::col_character() , # field_type is radio
#> vob11 = readr::col_character() , # field_type is radio
#> vob12 = readr::col_character() , # field_type is radio
#> vob13 = readr::col_character() , # field_type is radio
#> vob14 = readr::col_character() , # field_type is note
#> visit_observed_behavior_complete = readr::col_integer() , # completion status of form/instrument
#> study_comments = readr::col_character() , # field_type is note
#> complete_study = readr::col_character() , # field_type is dropdown
#> withdraw_date = readr::col_date() , # validation is 'date_ymd'
#> date_visit_4 = readr::col_date() , # validation is 'date_ymd'
#> alb_4 = readr::col_double() , # validation is 'number'
#> prealb_4 = readr::col_double() , # validation is 'number'
#> creat_4 = readr::col_date() , # validation is 'date_ymd'
#> discharge_date_4 = readr::col_date() , # validation is 'date_ymd'
#> discharge_summary_4 = readr::col_character() , # field_type is dropdown
#> npcr_4 = readr::col_integer() , # validation is 'integer'
#> chol_4 = readr::col_integer() , # validation is 'integer'
#> withdraw_reason = readr::col_character() , # field_type is dropdown
#> completion_data_complete = readr::col_integer() , # completion status of form/instrument
#> cpq1 = readr::col_date() , # validation is 'date_ymd'
#> cpq2 = readr::col_integer() , # validation is 'integer'
#> cpq3 = readr::col_integer() , # validation is 'integer'
#> cpq4 = readr::col_integer() , # validation is 'integer'
#> cpq5 = readr::col_integer() , # validation is 'integer'
#> cpq6 = readr::col_character() , # field_type is dropdown
#> cpq7 = readr::col_character() , # field_type is dropdown
#> cpq8 = readr::col_character() , # field_type is dropdown
#> cpq9 = readr::col_date() , # validation is 'date_ymd'
#> cpq10 = readr::col_character() , # field_type is dropdown
#> cpq11 = readr::col_character() , # field_type is dropdown
#> cpq12 = readr::col_character() , # field_type is radio
#> cpq13 = readr::col_character() , # field_type is dropdown
#> completion_project_questionnaire_complete = readr::col_integer() , # completion status of form/instrument
#> )
redcap_read_oneshot(uri, token, col_types = col_types)$data
#> 18 records and 125 columns were read from REDCap in 0.2 seconds. The http status code was 200.
#> # A tibble: 18 × 125
#> study_id redcap_event_name date_enrolled patient_document first_name
#> <chr> <chr> <date> <chr> <chr>
#> 1 100 enrollment_arm_1 2015-04-02 NA Zharko
#> 2 100 dose_1_arm_1 NA NA NA
#> 3 100 visit_1_arm_1 NA NA NA
#> 4 100 dose_2_arm_1 NA NA NA
#> 5 100 visit_2_arm_1 NA NA NA
#> 6 100 final_visit_arm_1 NA NA NA
#> 7 220 enrollment_arm_1 2015-04-02 NA Milivoj
#> 8 220 dose_1_arm_1 NA NA NA
#> 9 220 visit_1_arm_1 NA NA NA
#> 10 220 dose_2_arm_1 NA NA NA
#> 11 220 visit_2_arm_1 NA NA NA
#> 12 220 final_visit_arm_1 NA NA NA
#> 13 304 enrollment_arm_2 2015-04-02 levon_and_barry.j… Melech
#> 14 304 deadline_to_opt_ou_arm_2 NA NA NA
#> 15 304 first_dose_arm_2 NA NA NA
#> 16 304 first_visit_arm_2 NA NA NA
#> 17 304 final_visit_arm_2 NA NA NA
#> 18 304 deadline_to_return_arm_2 NA NA NA
#> # ℹ 120 more variables: last_name <chr>, telephone_1 <chr>, email <chr>,
#> # dob <date>, age <chr>, ethnicity <chr>, race <chr>, sex <chr>,
#> # given_birth <lgl>, num_children <int>, gym___0 <lgl>, gym___1 <lgl>,
#> # gym___2 <lgl>, gym___3 <lgl>, gym___4 <lgl>, aerobics___0 <lgl>,
#> # aerobics___1 <lgl>, aerobics___2 <lgl>, aerobics___3 <lgl>,
#> # aerobics___4 <lgl>, eat___0 <lgl>, eat___1 <lgl>, eat___2 <lgl>,
#> # eat___3 <lgl>, eat___4 <lgl>, drink___0 <lgl>, drink___1 <lgl>, …
# A repeating instruments project
token <- "64720C527CA236880FBA785C9934F02A" # repeating-instruments-sparse
col_types <- redcap_metadata_coltypes(uri, token)
#> # col_types <- readr::cols_only( # Use `readr::cols_only()` to restrict the retrieval to only these columns
#> col_types <- readr::cols( # Use `readr::cols()` to include unspecified columns
#> # [field] [readr col_type] [explanation for col_type]
#> record_id = readr::col_integer() , # record_autonumbering is enabled and DAGs are disabled for the project
#> redcap_repeat_instrument = readr::col_character() , # repeat_instrument
#> redcap_repeat_instance = readr::col_integer() , # repeat_instance
#> date_enrolled = readr::col_date() , # validation is 'date_ymd'
#> first_name = readr::col_character() , # field_type is text and validation isn't set
#> dob = readr::col_date() , # validation is 'date_ymd'
#> age = readr::col_character() , # field_type is text and validation isn't set
#> ethnicity = readr::col_character() , # field_type is radio
#> race = readr::col_character() , # field_type is dropdown
#> sex = readr::col_character() , # field_type is radio
#> demographics_complete = readr::col_integer() , # completion status of form/instrument
#> date_bp = readr::col_date() , # validation is 'date_ymd'
#> bp_systolic = readr::col_integer() , # validation is 'integer'
#> bp_diastolic = readr::col_integer() , # validation is 'integer'
#> bp_complete = readr::col_integer() , # completion status of form/instrument
#> )
redcap_read_oneshot(uri, token, col_types = col_types)$data
#> 9 records and 15 columns were read from REDCap in 0.2 seconds. The http status code was 200.
#> # A tibble: 9 × 15
#> record_id redcap_repeat_instrument redcap_repeat_instance date_enrolled
#> <int> <chr> <int> <date>
#> 1 1 NA NA 2019-10-14
#> 2 1 bp 1 NA
#> 3 1 bp 2 NA
#> 4 1 bp 3 NA
#> 5 2 NA NA 2019-02-02
#> 6 2 bp 1 NA
#> 7 3 NA NA 2021-11-04
#> 8 4 NA NA 2021-11-04
#> 9 5 NA NA NA
#> # ℹ 11 more variables: first_name <chr>, dob <date>, age <chr>,
#> # ethnicity <chr>, race <chr>, sex <chr>, demographics_complete <int>,
#> # date_bp <date>, bp_systolic <int>, bp_diastolic <int>, bp_complete <int>
# A project with every field type and validation type.
# Notice it throws a warning that some fields use a comma for a decimal,
# while other fields use a period/dot as a decimal
token <- "EB1FD5DDE583364AE605629AB7619397" # validation-types-1
col_types <- redcap_metadata_coltypes(uri, token)
#> Warning: The metadata for the REDCap project has validation types for at least one field that specifies a comma for a decimal for at least one field that specifies a period for a decimal. Mixing these two formats in the same project can cause confusion and problems. Consider passing `readr::col_character()` for this field (to REDCapR's `col_types` parameter) and then convert the desired fields to R's numeric type. The function `readr::parse_double()` is useful for this.
#> # col_types <- readr::cols_only( # Use `readr::cols_only()` to restrict the retrieval to only these columns
#> col_types <- readr::cols( # Use `readr::cols()` to include unspecified columns
#> # [field] [readr col_type] [explanation for col_type]
#> record_id = readr::col_integer() , # record_autonumbering is enabled and DAGs are disabled for the project
#> f_calculated = readr::col_character() , # field_type is calc
#> f_checkbox___0 = readr::col_logical() , # field_type is checkbox
#> f_checkbox___1 = readr::col_logical() , # field_type is checkbox
#> f_checkbox___2 = readr::col_logical() , # field_type is checkbox
#> f_dropdown = readr::col_character() , # field_type is dropdown
#> f_file_upload = readr::col_character() , # field_type is file
#> f_notes = readr::col_character() , # field_type is note
#> f_radio = readr::col_character() , # field_type is radio
#> f_signature = readr::col_character() , # field_type is file
#> f_slider = readr::col_integer() , # field_type is slider
#> f_sql = readr::col_character() , # field_type is sql
#> f_text = readr::col_character() , # field_type is text and validation isn't set
#> f_true_false = readr::col_logical() , # field_type is truefalse
#> f_yes_no = readr::col_logical() , # field_type is yesno
#> v_alpha_only = readr::col_character() , # validation is 'alpha_only'
#> v_date_dmy = readr::col_date() , # validation is 'date_dmy'
#> v_date_mdy = readr::col_date() , # validation is 'date_mdy'
#> v_date_ymd = readr::col_date() , # validation is 'date_ymd'
#> v_datetime_dmy = readr::col_datetime("%Y-%m-%d %H:%M") , # validation is 'datetime_dmy'
#> v_datetime_mdy = readr::col_datetime("%Y-%m-%d %H:%M") , # validation is 'datetime_mdy'
#> v_datetime_seconds_dmy = readr::col_datetime("%Y-%m-%d %H:%M:%S") , # validation is 'datetime_seconds_dmy'
#> v_datetime_seconds_mdy = readr::col_datetime("%Y-%m-%d %H:%M:%S") , # validation is 'datetime_seconds_mdy'
#> v_datetime_seconds_ymd = readr::col_datetime("%Y-%m-%d %H:%M:%S") , # validation is 'datetime_seconds_ymd'
#> v_datetime_ymd = readr::col_datetime("%Y-%m-%d %H:%M") , # validation is 'datetime_ymd'
#> v_email = readr::col_character() , # validation is 'email'
#> v_integer = readr::col_integer() , # validation is 'integer'
#> v_mrn_10d = readr::col_character() , # validation is 'mrn_10d'
#> v_mrn_generic = readr::col_character() , # validation is 'mrn_generic'
#> v_number = readr::col_double() , # validation is 'number'
#> v_number_1dp = readr::col_double() , # validation is 'number_1dp'
#> v_number_2dp = readr::col_double() , # validation is 'number_2dp'
#> v_number_3dp = readr::col_double() , # validation is 'number_3dp'
#> v_number_4dp = readr::col_double() , # validation is 'number_4dp'
#> v_number_comma_decimal = readr::col_character() , # locale's decimal mark isn't a comma, yet validation is 'number_comma_decimal'
#> v_number_1dp_comma_decimal = readr::col_character() , # locale's decimal mark isn't a comma, yet validation is 'number_1dp_comma_decimal'
#> v_number_2dp_comma_decimal = readr::col_character() , # locale's decimal mark isn't a comma, yet validation is 'number_2dp_comma_decimal'
#> v_number_3dp_comma_decimal = readr::col_character() , # locale's decimal mark isn't a comma, yet validation is 'number_3dp_comma_decimal'
#> v_number_4dp_comma_decimal = readr::col_character() , # locale's decimal mark isn't a comma, yet validation is 'number_4dp_comma_decimal'
#> v_phone = readr::col_character() , # validation is 'phone'
#> v_phone_australia = readr::col_character() , # validation is 'phone_australia'
#> v_postalcode_australia = readr::col_character() , # validation is 'postalcode_australia'
#> v_postalcode_canada = readr::col_character() , # validation is 'postalcode_canada'
#> v_postalcode_french = readr::col_character() , # validation is 'postalcode_french'
#> v_postalcode_germany = readr::col_character() , # validation is 'postalcode_germany'
#> v_ssn = readr::col_character() , # validation is 'ssn'
#> v_time_hh_mm = readr::col_time("%H:%M") , # validation is 'time'
#> v_time_hh_mm_ss = readr::col_time("%H:%M:%S") , # validation is 'time_hh_mm_ss'
#> v_time_mm_ss = readr::col_time("%M:%S") , # validation is 'time_mm_ss'
#> v_vmrn = readr::col_character() , # validation is 'vmrn'
#> v_zipcode = readr::col_character() , # validation is 'zipcode'
#> form_1_complete = readr::col_integer() , # completion status of form/instrument
#> )
redcap_read_oneshot(uri, token, col_types = col_types)$data
#> 1 records and 52 columns were read from REDCap in 0.2 seconds. The http status code was 200.
#> # A tibble: 1 × 52
#> record_id f_calculated f_checkbox___0 f_checkbox___1 f_checkbox___2 f_dropdown
#> <int> <chr> <lgl> <lgl> <lgl> <chr>
#> 1 1 7 FALSE FALSE FALSE NA
#> # ℹ 46 more variables: f_file_upload <chr>, f_notes <chr>, f_radio <chr>,
#> # f_signature <chr>, f_slider <int>, f_sql <chr>, f_text <chr>,
#> # f_true_false <lgl>, f_yes_no <lgl>, v_alpha_only <chr>, v_date_dmy <date>,
#> # v_date_mdy <date>, v_date_ymd <date>, v_datetime_dmy <dttm>,
#> # v_datetime_mdy <dttm>, v_datetime_seconds_dmy <dttm>,
#> # v_datetime_seconds_mdy <dttm>, v_datetime_seconds_ymd <dttm>,
#> # v_datetime_ymd <dttm>, v_email <chr>, v_integer <int>, v_mrn_10d <chr>, …
# }