.Rbuildignore

@@ -17,5 +17,3 @@
 ^CRAN-SUBMISSION$
 drafting
 app
-^\.lintr$
-^CODE_OF_CONDUCT\.md$

.lintr

@@ -1,7 +0,0 @@
-linters: linters_with_defaults(
-    commented_code_linter = NULL
-  )
-encoding: "UTF-8"
-exclusions: list(
-    "drafting/"
-  )

CODE_OF_CONDUCT.md

@@ -1,126 +0,0 @@
-# Contributor Covenant Code of Conduct
-
-## Our Pledge
-
-We as members, contributors, and leaders pledge to make participation in our
-community a harassment-free experience for everyone, regardless of age, body
-size, visible or invisible disability, ethnicity, sex characteristics, gender
-identity and expression, level of experience, education, socio-economic status,
-nationality, personal appearance, race, caste, color, religion, or sexual
-identity and orientation.
-
-We pledge to act and interact in ways that contribute to an open, welcoming,
-diverse, inclusive, and healthy community.
-
-## Our Standards
-
-Examples of behavior that contributes to a positive environment for our
-community include:
-
-* Demonstrating empathy and kindness toward other people
-* Being respectful of differing opinions, viewpoints, and experiences
-* Giving and gracefully accepting constructive feedback
-* Accepting responsibility and apologizing to those affected by our mistakes,
-  and learning from the experience
-* Focusing on what is best not just for us as individuals, but for the overall
-  community
-
-Examples of unacceptable behavior include:
-
-* The use of sexualized language or imagery, and sexual attention or advances of
-  any kind
-* Trolling, insulting or derogatory comments, and personal or political attacks
-* Public or private harassment
-* Publishing others' private information, such as a physical or email address,
-  without their explicit permission
-* Other conduct which could reasonably be considered inappropriate in a
-  professional setting
-
-## Enforcement Responsibilities
-
-Community leaders are responsible for clarifying and enforcing our standards of
-acceptable behavior and will take appropriate and fair corrective action in
-response to any behavior that they deem inappropriate, threatening, offensive,
-or harmful.
-
-Community leaders have the right and responsibility to remove, edit, or reject
-comments, commits, code, wiki edits, issues, and other contributions that are
-not aligned to this Code of Conduct, and will communicate reasons for moderation
-decisions when appropriate.
-
-## Scope
-
-This Code of Conduct applies within all community spaces, and also applies when
-an individual is officially representing the community in public spaces.
-Examples of representing our community include using an official e-mail address,
-posting via an official social media account, or acting as an appointed
-representative at an online or offline event.
-
-## Enforcement
-
-Instances of abusive, harassing, or otherwise unacceptable behavior may be
-reported to the community leaders responsible for enforcement at andreas@gdamsbo.dk. 
-All complaints will be reviewed and investigated promptly and fairly.
-
-All community leaders are obligated to respect the privacy and security of the
-reporter of any incident.
-
-## Enforcement Guidelines
-
-Community leaders will follow these Community Impact Guidelines in determining
-the consequences for any action they deem in violation of this Code of Conduct:
-
-### 1. Correction
-
-**Community Impact**: Use of inappropriate language or other behavior deemed
-unprofessional or unwelcome in the community.
-
-**Consequence**: A private, written warning from community leaders, providing
-clarity around the nature of the violation and an explanation of why the
-behavior was inappropriate. A public apology may be requested.
-
-### 2. Warning
-
-**Community Impact**: A violation through a single incident or series of
-actions.
-
-**Consequence**: A warning with consequences for continued behavior. No
-interaction with the people involved, including unsolicited interaction with
-those enforcing the Code of Conduct, for a specified period of time. This
-includes avoiding interactions in community spaces as well as external channels
-like social media. Violating these terms may lead to a temporary or permanent
-ban.
-
-### 3. Temporary Ban
-
-**Community Impact**: A serious violation of community standards, including
-sustained inappropriate behavior.
-
-**Consequence**: A temporary ban from any sort of interaction or public
-communication with the community for a specified period of time. No public or
-private interaction with the people involved, including unsolicited interaction
-with those enforcing the Code of Conduct, is allowed during this period.
-Violating these terms may lead to a permanent ban.
-
-### 4. Permanent Ban
-
-**Community Impact**: Demonstrating a pattern of violation of community
-standards, including sustained inappropriate behavior, harassment of an
-individual, or aggression toward or disparagement of classes of individuals.
-
-**Consequence**: A permanent ban from any sort of public interaction within the
-community.
-
-## Attribution
-
-This Code of Conduct is adapted from the [Contributor Covenant][homepage],
-version 2.1, available at
-<https://www.contributor-covenant.org/version/2/1/code_of_conduct.html>.
-
-Community Impact Guidelines were inspired by
-[Mozilla's code of conduct enforcement ladder][https://github.com/mozilla/inclusion].
-
-For answers to common questions about this code of conduct, see the FAQ at
-<https://www.contributor-covenant.org/faq>. Translations are available at <https://www.contributor-covenant.org/translations>.
-
-[homepage]: https://www.contributor-covenant.org

DESCRIPTION

@@ -30,10 +30,14 @@ Suggests:
     gt,
     usethis,
     ggplot2,
+    haven,
     here,
     styler,
     devtools,
     roxygen2,
+    openxlsx2,
+    rsconnect,
+    shiny,
     spelling
 License: GPL (>= 3)
 Encoding: UTF-8
@@ -49,11 +53,7 @@ Imports:
     keyring,
     purrr,
     readr,
-    stats,
+    stats
-    shiny,
-    openxlsx2,
-    rsconnect,
-    haven
 Collate: 
     'utils.r'
     'process_user_input.r'

R/REDCap_split.r

@@ -24,19 +24,19 @@
 #'
 #' # Get the records
 #' records <- postForm(
-#'   uri = api_url, # Supply your site-specific URI
+#'   uri = api_url,     # Supply your site-specific URI
 #'   token = api_token, # Supply your own API token
-#'   content = "record",
+#'   content = 'record',
-#'   format = "json",
+#'   format = 'json',
-#'   returnFormat = "json"
+#'   returnFormat = 'json'
 #' )
 #'
 #' # Get the metadata
 #' metadata <- postForm(
-#'   uri = api_url, # Supply your site-specific URI
+#'   uri = api_url,     # Supply your site-specific URI
 #'   token = api_token, # Supply your own API token
-#'   content = "metadata",
+#'   content = 'metadata',
-#'   format = "json"
+#'   format = 'json'
 #' )
 #'
 #' # Convert exported JSON strings into a list of data.frames
@@ -49,8 +49,7 @@
 #'
 #' # Get the metadata
 #' metadata <- read.csv(
-#'   "/path/to/data/ExampleProject_DataDictionary_2018-06-03.csv"
+#' "/path/to/data/ExampleProject_DataDictionary_2018-06-03.csv")
-#' )
 #'
 #' # Split the tables
 #' REDCapRITS::REDCap_split(records, metadata)
@@ -87,8 +86,9 @@ REDCap_split <- function(records,
                          metadata,
                          primary_table_name = "",
                          forms = c("repeating", "all")) {
+
   # Process user input
-  records <- process_user_input(records)
+  records  <- process_user_input(records)
   metadata <-
     as.data.frame(process_user_input(metadata))
 
@@ -96,27 +96,26 @@ REDCap_split <- function(records,
   vars_in_data <- names(records)
 
   # Process repeat instrument names to match the redcap naming
-  if (is_repeated_longitudinal(records)) {
+  if (is_repeated_longitudinal(records)){
-    records$redcap_repeat_instrument <-
+  records$redcap_repeat_instrument <- clean_redcap_name(records$redcap_repeat_instrument)
-      clean_redcap_name(records$redcap_repeat_instrument)
 
-    # Match arg for forms
+  # Match arg for forms
-    forms <- match.arg(forms, c("repeating", "all"))
+  forms <- match.arg(forms, c("repeating", "all"))
 
-    # Check to see if there were any repeating instruments
+  # Check to see if there were any repeating instruments
-    if (forms == "repeating" &&
+  if (forms == "repeating" &&
       !"redcap_repeat_instrument" %in% vars_in_data) {
-      stop("There are no repeating instruments in this dataset.")
+    stop("There are no repeating instruments in this dataset.")
-    }
+  }
 
-    # Remove NAs from `redcap_repeat_instrument` (see issue #12)
+  # Remove NAs from `redcap_repeat_instrument` (see issue #12)
-    if (any(is.na(records$redcap_repeat_instrument))) {
+  if (any(is.na(records$redcap_repeat_instrument))) {
-      records$redcap_repeat_instrument <- ifelse(
+    records$redcap_repeat_instrument <- ifelse(
-        is.na(records$redcap_repeat_instrument),
+      is.na(records$redcap_repeat_instrument),
-        "",
+      "",
-        as.character(records$redcap_repeat_instrument)
+      as.character(records$redcap_repeat_instrument)
-      )
+    )
-    }
+  }
   }
 
   # Standardize variable names for metadata
@@ -145,9 +144,8 @@ REDCap_split <- function(records,
   if ("redcap_repeat_instrument" %in% vars_in_data) {
     # Variables to be at the beginning of each repeating instrument
     repeat_instrument_fields <- grep("^redcap_repeat.*",
-      vars_in_data,
+                                     vars_in_data,
-      value = TRUE
+                                     value = TRUE)
-    )
 
     # Identify the subtables in the data
     subtables <- unique(records$redcap_repeat_instrument)
@@ -171,36 +169,35 @@ REDCap_split <- function(records,
     # Delete the variables that are not relevant
     for (i in names(out)) {
       if (i == primary_table_name) {
-        out_fields <- which(vars_in_data %in% c(
+        out_fields <- which(vars_in_data %in% c(universal_fields,
-          universal_fields,
+                                                fields[!fields[, 2] %in%
-          fields[!fields[, 2] %in%
+                                                         subtables, 1]))
-            subtables, 1]
-        ))
         out[[primary_table_index]] <-
           out[[primary_table_index]][out_fields]
+
       } else {
-        out_fields <- which(vars_in_data %in% c(
+        out_fields <- which(vars_in_data %in% c(universal_fields,
-          universal_fields,
+                                                repeat_instrument_fields,
-          repeat_instrument_fields,
+                                                fields[fields[, 2] == i, 1]))
-          fields[fields[, 2] == i, 1]
-        ))
         out[[i]] <- out[[i]][out_fields]
+
       }
+
     }
 
     if (forms == "all") {
-      out <- c(
+      out <- c(split_non_repeating_forms(out[[primary_table_index]],
-        split_non_repeating_forms(
+                                         universal_fields,
-          out[[primary_table_index]],
+                                         fields[!fields[, 2] %in% subtables, ]),
-          universal_fields,
+               out[-primary_table_index])
-          fields[!fields[, 2] %in% subtables, ]
+
-        ),
-        out[-primary_table_index]
-      )
     }
+
   } else {
     out <- split_non_repeating_forms(records, universal_fields, fields)
+
   }
 
   out
 }
+

R/ds2dd.R

@@ -41,7 +41,7 @@ ds2dd <-
     dd <- data.frame(matrix(ncol = length(metadata), nrow = ncol(ds)))
     colnames(dd) <- metadata
 
-    if (is.character(record.id) && !record.id %in% colnames(ds)) {
+    if (is.character(record.id) & !record.id %in% colnames(ds)) {
       stop("Provided record.id is not a variable name in provided data set.")
     }
 
@@ -59,7 +59,7 @@ ds2dd <-
     dd[, "field_name"] <-
       c(field.name[colsel], field.name[!colsel])
 
-    if (length(form.name) > 1 && length(form.name) != ncol(ds)) {
+    if (length(form.name) > 1 & length(form.name) != ncol(ds)) {
       stop(
         "Provided form.name should be of length 1 (value is reused) or equal
         length as number of variables in data set."
@@ -67,7 +67,7 @@ ds2dd <-
     }
     dd[, "form_name"] <- form.name
 
-    if (length(field.type) > 1 && length(field.type) != ncol(ds)) {
+    if (length(field.type) > 1 & length(field.type) != ncol(ds)) {
       stop(
         "Provided field.type should be of length 1 (value is reused) or equal
         length as number of variables in data set."

R/ds2dd_detailed.R

@@ -1,9 +1,4 @@
-utils::globalVariables(c(
+utils::globalVariables(c(  "stats::setNames",  "field_name",  "field_type",  "select_choices_or_calculations"))
-  "stats::setNames",
-  "field_name",
-  "field_type",
-  "select_choices_or_calculations"
-))
 #' Try at determining which are true time only variables
 #'
 #' @description
@@ -23,15 +18,10 @@ utils::globalVariables(c(
 #' @examples
 #' data <- redcapcast_data
 #' data |> guess_time_only_filter()
-#' data |>
+#' data |> guess_time_only_filter(validate = TRUE) |> lapply(head)
-#'   guess_time_only_filter(validate = TRUE) |>
+guess_time_only_filter <- function(data, validate = FALSE, sel.pos = "[Tt]i[d(me)]", sel.neg = "[Dd]at[eo]") {
-#'   lapply(head)
-guess_time_only_filter <- function(data,
-                                   validate = FALSE,
-                                   sel.pos = "[Tt]i[d(me)]",
-                                   sel.neg = "[Dd]at[eo]") {
   datetime_nms <- data |>
-    lapply(\(x) any(c("POSIXct", "hms") %in% class(x))) |>
+    lapply(\(x)any(c("POSIXct","hms") %in% class(x))) |>
     (\(x) names(data)[do.call(c, x)])()
 
   time_only_log <- datetime_nms |> (\(x) {
@@ -52,8 +42,12 @@ guess_time_only_filter <- function(data,
   }
 }
 
-#' Correction based on time_only_filter function
+#' Correction based on time_only_filter function. Introduces new class for easier
+#' validation labelling.
 #'
+#' @description
+#' Dependens on the data class "hms" introduced with
+#' `guess_time_only_filter()` and converts these
 #'
 #' @param data data set
 #' @param ... arguments passed on to `guess_time_only_filter()`
@@ -125,8 +119,8 @@ hms2character <- function(data) {
 #' data set (imported .dta file with `haven::read_dta()`. Default is "label"
 #' @param field.validation manually specify field validation(s). Vector of
 #' length 1 or ncol(data). Default is NULL and `levels()` are used for factors
-#' or attribute `factor.labels.attr` for haven_labelled data set (imported .dta
+#' or attribute `factor.labels.attr` for haven_labelled data set (imported .dta file with
-#' file with `haven::read_dta()`).
+#' `haven::read_dta()`).
 #' @param metadata redcap metadata headings. Default is
 #' REDCapCAST:::metadata_names.
 #' @param validate.time Flag to validate guessed time columns
@@ -150,7 +144,7 @@ ds2dd_detailed <- function(data,
                            form.name = NULL,
                            field.type = NULL,
                            field.label = NULL,
-                           field.label.attr = "label",
+                           field.label.attr ="label",
                            field.validation = NULL,
                            metadata = metadata_names,
                            validate.time = FALSE,
@@ -170,8 +164,7 @@ ds2dd_detailed <- function(data,
   }
 
   if (lapply(data, haven::is.labelled) |> (\(x)do.call(c, x))() |> any()) {
-    message("Data seems to be imported with haven from a Stata (.dta) file and
+    message("Data seems to be imported with haven from a Stata (.dta) file and will be treated as such.")
-            will be treated as such.")
     data.source <- "dta"
   } else {
     data.source <- ""
@@ -179,25 +172,18 @@ ds2dd_detailed <- function(data,
 
   ## data classes
 
-  ### Only keeps the first class, as time fields (POSIXct/POSIXt) has two
+  ### Only keeps the first class, as time fields (POSIXct/POSIXt) has two classes
-  ### classes
   if (data.source == "dta") {
     data_classes <-
       data |>
       haven::as_factor() |>
-      time_only_correction(
+      time_only_correction(sel.pos = time.var.sel.pos, sel.neg = time.var.sel.neg) |>
-        sel.pos = time.var.sel.pos,
-        sel.neg = time.var.sel.neg
-      ) |>
       lapply(\(x)class(x)[1]) |>
       (\(x)do.call(c, x))()
   } else {
     data_classes <-
       data |>
-      time_only_correction(
+      time_only_correction(sel.pos = time.var.sel.pos, sel.neg = time.var.sel.neg) |>
-        sel.pos = time.var.sel.pos,
-        sel.neg = time.var.sel.neg
-      ) |>
       lapply(\(x)class(x)[1]) |>
       (\(x)do.call(c, x))()
   }
@@ -218,7 +204,7 @@ ds2dd_detailed <- function(data,
   if (is.null(form.name)) {
     dd$form_name <- "data"
   } else {
-    if (length(form.name) == 1 || length(form.name) == nrow(dd)) {
+    if (length(form.name) == 1 | length(form.name) == nrow(dd)) {
       dd$form_name <- form.name
     } else {
       stop("Length of supplied 'form.name' has to be one (1) or ncol(data).")
@@ -243,11 +229,9 @@ ds2dd_detailed <- function(data,
     }
 
     dd <-
-      dd |> dplyr::mutate(field_label = dplyr::if_else(is.na(label),
+      dd |> dplyr::mutate(field_label = dplyr::if_else(is.na(label), field_name, label))
-        field_name, label
-      ))
   } else {
-    if (length(field.label) == 1 || length(field.label) == nrow(dd)) {
+    if (length(field.label) == 1 | length(field.label) == nrow(dd)) {
       dd$field_label <- field.label
     } else {
       stop("Length of supplied 'field.label' has to be one (1) or ncol(data).")
@@ -261,11 +245,9 @@ ds2dd_detailed <- function(data,
     dd$field_type <- "text"
 
     dd <-
-      dd |> dplyr::mutate(field_type = dplyr::if_else(data_classes == "factor",
+      dd |> dplyr::mutate(field_type = dplyr::if_else(data_classes == "factor", "radio", field_type))
-        "radio", field_type
-      ))
   } else {
-    if (length(field.type) == 1 || length(field.type) == nrow(dd)) {
+    if (length(field.type) == 1 | length(field.type) == nrow(dd)) {
       dd$field_type <- field.type
     } else {
       stop("Length of supplied 'field.type' has to be one (1) or ncol(data).")
@@ -289,11 +271,10 @@ ds2dd_detailed <- function(data,
         )
       )
   } else {
-    if (length(field.validation) == 1 || length(field.validation) == nrow(dd)) {
+    if (length(field.validation) == 1 | length(field.validation) == nrow(dd)) {
       dd$text_validation_type_or_show_slider_number <- field.validation
     } else {
-      stop("Length of supplied 'field.validation'
+      stop("Length of supplied 'field.validation' has to be one (1) or ncol(data).")
-           has to be one (1) or ncol(data).")
     }
   }
 
@@ -319,13 +300,7 @@ ds2dd_detailed <- function(data,
           ## Re-factors to avoid confusion with missing levels
           ## Assumes alle relevant levels are represented in the data
           re_fac <- factor(x)
-          paste(
+          paste(paste(unique(as.numeric(re_fac)), levels(re_fac), sep = ", "), collapse = " | ")
-            paste(unique(as.numeric(re_fac)),
-              levels(re_fac),
-              sep = ", "
-            ),
-            collapse = " | "
-          )
         } else {
           NA
         }
@@ -344,10 +319,7 @@ ds2dd_detailed <- function(data,
 
   list(
     data = data |>
-      time_only_correction(
+      time_only_correction(sel.pos = time.var.sel.pos, sel.neg = time.var.sel.neg) |>
-        sel.pos = time.var.sel.pos,
-        sel.neg = time.var.sel.neg
-      ) |>
       hms2character() |>
       (\(x)stats::setNames(x, tolower(names(x))))(),
     meta = dd
@@ -361,16 +333,11 @@ ds2dd_detailed <- function(data,
 #' @param ls output list from `ds2dd_detailed()`
 #'
 #' @return list with `REDCapR::redcap_write()` results
-mark_complete <- function(upload, ls) {
+mark_complete <- function(upload, ls){
   data <- ls$data
   meta <- ls$meta
   forms <- unique(meta$form_name)
-  cbind(
+  cbind(data[[1]][data[[1]] %in% upload$affected_ids],
-    data[[1]][data[[1]] %in% upload$affected_ids],
+        data.frame(matrix(2,ncol=length(forms),nrow=upload$records_affected_count))) |>
-    data.frame(matrix(2,
+    stats::setNames(c(names(data)[1],paste0(forms,"_complete")))
-      ncol = length(forms),
-      nrow = upload$records_affected_count
-    ))
-  ) |>
-    stats::setNames(c(names(data)[1], paste0(forms, "_complete")))
 }

R/easy_redcap.R

@@ -1,3 +1,4 @@
+
 #' Retrieve project API key if stored, if not, set and retrieve
 #'
 #' @param key.name character vector of key name
@@ -25,7 +26,7 @@ get_api_key <- function(key.name) {
 #'
 #' @return data.frame or list depending on widen.data
 #' @export
-easy_redcap <- function(project.name, widen.data = TRUE, uri, ...) {
+easy_redcap <- function(project.name, widen.data=TRUE, uri, ...) {
   key <- get_api_key(key.name = paste0(project.name, "_REDCAP_API"))
 
   out <- read_redcap_tables(
@@ -34,7 +35,7 @@ easy_redcap <- function(project.name, widen.data = TRUE, uri, ...) {
     ...
   )
 
-  if (widen.data) {
+  if (widen.data){
     out <- out |> redcap_wider()
   }
 

R/mtcars_redcap.R

@@ -20,3 +20,4 @@
 #' }
 #' @usage data(mtcars_redcap)
 "mtcars_redcap"
+

R/process_user_input.r

@@ -1,4 +1,4 @@
-process_user_input <- function(x) {
+process_user_input <- function (x) {
   UseMethod("process_user_input", x)
 }
 
@@ -30,8 +30,10 @@ process_user_input.character <- function(x, ...) {
   }
 
   jsonlite::fromJSON(x)
+
 }
 
 process_user_input.response <- function(x, ...) {
   process_user_input(rawToChar(x$content))
+
 }

R/read_redcap_instrument.R

@@ -1,22 +1,20 @@
-#' Convenience function to download complete instrument, using token storage
+#' Convenience function to download complete instrument, using token storage in keyring.
-#' in keyring.
 #'
 #' @param key key name in standard keyring for token retrieval.
 #' @param uri REDCap database API uri
 #' @param instrument instrument name
 #' @param raw_or_label raw or label passed to `REDCapR::redcap_read()`
 #' @param id_name id variable name. Default is "record_id".
-#' @param records specify the records to download. Index numbers.
+#' @param records specify the records to download. Index numbers. Numeric vector.
-#' Numeric vector.
 #'
 #' @return data.frame
 #' @export
 read_redcap_instrument <- function(key,
-                                   uri,
+                            uri,
-                                   instrument,
+                            instrument,
-                                   raw_or_label = "raw",
+                            raw_or_label = "raw",
-                                   id_name = "record_id",
+                            id_name = "record_id",
-                                   records = NULL) {
+                            records = NULL) {
   REDCapCAST::read_redcap_tables(
     records = records,
     uri = uri, token = keyring::key_get(key),

R/read_redcap_tables.R

@@ -38,8 +38,7 @@ read_redcap_tables <- function(uri,
     fields_test <- fields %in% unique(m$field_name)
 
     if (any(!fields_test)) {
-      print(paste0("The following field names are invalid: ",
+      print(paste0("The following field names are invalid: ", paste(fields[!fields_test], collapse = ", "), "."))
-                   paste(fields[!fields_test], collapse = ", "), "."))
       stop("Not all supplied field names are valid")
     }
   }
@@ -49,8 +48,7 @@ read_redcap_tables <- function(uri,
     forms_test <- forms %in% unique(m$form_name)
 
     if (any(!forms_test)) {
-      print(paste0("The following form names are invalid: ",
+      print(paste0("The following form names are invalid: ", paste(forms[!forms_test], collapse = ", "), "."))
-                   paste(forms[!forms_test], collapse = ", "), "."))
       stop("Not all supplied form names are valid")
     }
   }
@@ -64,8 +62,7 @@ read_redcap_tables <- function(uri,
     event_test <- events %in% unique(arm_event_inst$data$unique_event_name)
 
     if (any(!event_test)) {
-      print(paste0("The following event names are invalid: ",
+      print(paste0("The following event names are invalid: ", paste(events[!event_test], collapse = ", "), "."))
-                   paste(events[!event_test], collapse = ", "), "."))
       stop("Not all supplied event names are valid")
     }
   }
@@ -92,12 +89,15 @@ read_redcap_tables <- function(uri,
   m <- focused_metadata(m, names(d))
 
 
-  # Splitting
+    # Splitting
-  out <- REDCap_split(d,
+    out <- REDCap_split(d,
-    m,
+      m,
-    forms = split_forms,
+      forms = split_forms,
-    primary_table_name = ""
+      primary_table_name = ""
-  )
+    )
+
+    sanitize_split(out)
 
-  sanitize_split(out)
 }
+
+

R/redcap_wider.R

@@ -1,8 +1,6 @@
-utils::globalVariables(c(
+utils::globalVariables(c("redcap_wider",
-  "redcap_wider",
+"event.glue",
-  "event.glue",
+"inst.glue"))
-  "inst.glue"
-))
 
 #' @title Redcap Wider
 #' @description Converts a list of REDCap data frames from long to wide format.
@@ -18,65 +16,42 @@ utils::globalVariables(c(
 #'
 #' @examples
 #' # Longitudinal
-#' list1 <- list(
+#' list1 <- list(data.frame(record_id = c(1,2,1,2),
-#'   data.frame(
+#' redcap_event_name = c("baseline", "baseline", "followup", "followup"),
-#'     record_id = c(1, 2, 1, 2),
+#' age = c(25,26,27,28)),
-#'     redcap_event_name = c("baseline", "baseline", "followup", "followup"),
+#' data.frame(record_id = c(1,2),
-#'     age = c(25, 26, 27, 28)
+#' redcap_event_name = c("baseline", "baseline"),
-#'   ),
+#' gender = c("male", "female")))
-#'   data.frame(
-#'     record_id = c(1, 2),
-#'     redcap_event_name = c("baseline", "baseline"),
-#'     gender = c("male", "female")
-#'   )
-#' )
 #' redcap_wider(list1)
 #' # Simpel with two instruments
-#' list2 <- list(
+#' list2 <- list(data.frame(record_id = c(1,2),
-#'   data.frame(
+#' age = c(25,26)),
-#'     record_id = c(1, 2),
+#' data.frame(record_id = c(1,2),
-#'     age = c(25, 26)
+#' gender = c("male", "female")))
-#'   ),
-#'   data.frame(
-#'     record_id = c(1, 2),
-#'     gender = c("male", "female")
-#'   )
-#' )
 #' redcap_wider(list2)
 #' # Simple with single instrument
-#' list3 <- list(data.frame(
+#' list3 <- list(data.frame(record_id = c(1,2),
-#'   record_id = c(1, 2),
+#' age = c(25,26)))
-#'   age = c(25, 26)
-#' ))
 #' redcap_wider(list3)
 #' # Longitudinal with repeatable instruments
-#' list4 <- list(
+#' list4 <- list(data.frame(record_id = c(1,2,1,2),
-#'   data.frame(
+#' redcap_event_name = c("baseline", "baseline", "followup", "followup"),
-#'     record_id = c(1, 2, 1, 2),
+#' age = c(25,26,27,28)),
-#'     redcap_event_name = c("baseline", "baseline", "followup", "followup"),
+#' data.frame(record_id = c(1,1,1,1,2,2,2,2),
-#'     age = c(25, 26, 27, 28)
+#' redcap_event_name = c("baseline", "baseline", "followup", "followup",
-#'   ),
+#' "baseline", "baseline", "followup", "followup"),
-#'   data.frame(
+#' redcap_repeat_instrument = "walk",
-#'     record_id = c(1, 1, 1, 1, 2, 2, 2, 2),
+#' redcap_repeat_instance=c(1,2,1,2,1,2,1,2),
-#'     redcap_event_name = c(
+#' dist = c(40, 32, 25, 33, 28, 24, 23, 36)),
-#'       "baseline", "baseline", "followup", "followup",
+#' data.frame(record_id = c(1,2),
-#'       "baseline", "baseline", "followup", "followup"
+#' redcap_event_name = c("baseline", "baseline"),
-#'     ),
+#' gender = c("male", "female")))
-#'     redcap_repeat_instrument = "walk",
+#'redcap_wider(list4)
-#'     redcap_repeat_instance = c(1, 2, 1, 2, 1, 2, 1, 2),
-#'     dist = c(40, 32, 25, 33, 28, 24, 23, 36)
-#'   ),
-#'   data.frame(
-#'     record_id = c(1, 2),
-#'     redcap_event_name = c("baseline", "baseline"),
-#'     gender = c("male", "female")
-#'   )
-#' )
-#' redcap_wider(list4)
 redcap_wider <-
   function(data,
            event.glue = "{.value}_{redcap_event_name}",
            inst.glue = "{.value}_{redcap_repeat_instance}") {
+
     if (!is_repeated_longitudinal(data)) {
       if (is.list(data)) {
         if (length(data) == 1) {
@@ -84,65 +59,69 @@ redcap_wider <-
         } else {
           out <- data |> purrr::reduce(dplyr::left_join)
         }
-      } else if (is.data.frame(data)) {
+      } else if (is.data.frame(data)){
         out <- data
       }
+
+
     } else {
-      id.name <- do.call(c, lapply(data, names))[[1]]
 
-      l <- lapply(data, function(i) {
+    id.name <- do.call(c, lapply(data, names))[[1]]
-        rep_inst <- "redcap_repeat_instrument" %in% names(i)
 
-        if (rep_inst) {
+    l <- lapply(data, function(i) {
-          k <- lapply(split(i, f = i[[id.name]]), function(j) {
+      rep_inst <- "redcap_repeat_instrument" %in% names(i)
-            cname <- colnames(j)
-            vals <-
-              cname[!cname %in% c(
-                id.name,
-                "redcap_event_name",
-                "redcap_repeat_instrument",
-                "redcap_repeat_instance"
-              )]
-            s <- tidyr::pivot_wider(
-              j,
-              names_from = "redcap_repeat_instance",
-              values_from = all_of(vals),
-              names_glue = inst.glue
-            )
-            s[!colnames(s) %in% c("redcap_repeat_instrument")]
-          })
-          i <- Reduce(dplyr::bind_rows, k)
-        }
 
-        event <- "redcap_event_name" %in% names(i)
+      if (rep_inst) {
+        k <- lapply(split(i, f = i[[id.name]]), function(j) {
+          cname <- colnames(j)
+          vals <-
+            cname[!cname %in% c(
+              id.name,
+              "redcap_event_name",
+              "redcap_repeat_instrument",
+              "redcap_repeat_instance"
+            )]
+          s <- tidyr::pivot_wider(
+            j,
+            names_from = "redcap_repeat_instance",
+            values_from = all_of(vals),
+            names_glue = inst.glue
+          )
+          s[!colnames(s) %in% c("redcap_repeat_instrument")]
+        })
+        i <- Reduce(dplyr::bind_rows, k)
+      }
 
-        if (event) {
+      event <- "redcap_event_name" %in% names(i)
-          event.n <- length(unique(i[["redcap_event_name"]])) > 1
 
-          i[["redcap_event_name"]] <-
+      if (event) {
-            gsub(" ", "_", tolower(i[["redcap_event_name"]]))
+        event.n <- length(unique(i[["redcap_event_name"]])) > 1
 
-          if (event.n) {
+        i[["redcap_event_name"]] <-
-            cname <- colnames(i)
+          gsub(" ", "_", tolower(i[["redcap_event_name"]]))
-            vals <- cname[!cname %in% c(id.name, "redcap_event_name")]
 
-            s <- tidyr::pivot_wider(
+        if (event.n) {
-              i,
+          cname <- colnames(i)
-              names_from = "redcap_event_name",
+          vals <- cname[!cname %in% c(id.name, "redcap_event_name")]
-              values_from = all_of(vals),
+
-              names_glue = event.glue
+          s <- tidyr::pivot_wider(
-            )
+            i,
-            s[colnames(s) != "redcap_event_name"]
+            names_from = "redcap_event_name",
-          } else {
+            values_from = all_of(vals),
-            i[colnames(i) != "redcap_event_name"]
+            names_glue = event.glue
-          }
+          )
+          s[colnames(s) != "redcap_event_name"]
         } else {
-          i
+          i[colnames(i) != "redcap_event_name"]
+          }
+      } else {
+        i
         }
-      })
+    })
 
-      out <- data.frame(Reduce(f = dplyr::full_join, x = l))
+    out <- data.frame(Reduce(f = dplyr::full_join, x = l))
     }
 
     out
   }
+

R/redcapcast_data.R

@@ -33,3 +33,5 @@
 #' }
 #' @usage data(redcapcast_data)
 "redcapcast_data"
+
+

R/redcapcast_meta.R

@@ -25,3 +25,5 @@
 #' }
 #' @usage data(redcapcast_meta)
 "redcapcast_meta"
+
+

R/shiny_cast.R

@@ -14,7 +14,8 @@ server_factory <- function() {
 #' @export
 ui_factory <- function() {
   # require(ggplot2)
-  source(here::here("app/ui.R"))
+source(here::here("app/ui.R"))
+
 }
 
 #' Launch the included Shiny-app for database casting and upload
@@ -45,7 +46,7 @@ shiny_cast <- function() {
 #' @examples
 #' # deploy_shiny
 #'
-deploy_shiny <- function(path = here::here("app/"), name.app = "shiny_cast") {
+deploy_shiny <- function(path=here::here("app/"), name.app="shiny_cast"){
   # Connecting
   rsconnect::setAccountInfo(
     name = "cognitiveindex",
@@ -54,5 +55,5 @@ deploy_shiny <- function(path = here::here("app/"), name.app = "shiny_cast") {
   )
 
   # Deploying
-  rsconnect::deployApp(appDir = path, lint = TRUE, appName = name.app, )
+  rsconnect::deployApp(appDir = path,lint = TRUE,appName = name.app,)
 }

R/utils.r

@@ -128,11 +128,9 @@ sanitize_split <- function(l,
                              "redcap_repeat_instrument",
                              "redcap_repeat_instance"
                            )) {
-  generic.names <- c(
+  generic.names <- c(get_id_name(l),
-    get_id_name(l),
+                     generic.names,
-    generic.names,
+                     paste0(names(l), "_complete"))
-    paste0(names(l), "_complete")
-  )
 
   lapply(l, function(i) {
     if (ncol(i) > 2) {
@@ -336,8 +334,7 @@ split_non_repeating_forms <-
 #' @export
 #'
 #' @examples
-#' test <- c("12 months follow-up", "3 steps", "mRS 6 weeks",
+#' test <- c("12 months follow-up", "3 steps", "mRS 6 weeks", "Counting to 231 now")
-#' "Counting to 231 now")
 #' strsplitx(test, "[0-9]", type = "around")
 strsplitx <- function(x,
                       split,
@@ -406,8 +403,7 @@ d2w <- function(x, lang = "en", neutrum = FALSE, everything = FALSE) {
   # In Danish the written 1 depends on the counted word
   if (neutrum) nt <- "t" else nt <- "n"
 
-  # A sapply() call with nested lapply() to handle vectors, data.frames
+  # A sapply() call with nested lapply() to handle vectors, data.frames and lists
-  # and lists
   convert <- function(x, lang, neutrum) {
     zero_nine <- data.frame(
       num = 0:9,
@@ -507,9 +503,7 @@ is_repeated_longitudinal <- function(data, generics = c(
 #' @examples
 #' file_extension(list.files(here::here(""))[[2]])[[1]]
 file_extension <- function(filenames) {
-  sub(pattern = "^(.*\\.|[^.]+)(?=[^.]*)", replacement = "",
+  sub(pattern = "^(.*\\.|[^.]+)(?=[^.]*)", replacement = "", filenames, perl = TRUE)
-      filenames,
-      perl = TRUE)
 }
 
 #' Flexible file import based on extension
@@ -522,16 +516,17 @@ file_extension <- function(filenames) {
 #'
 #' @examples
 #' read_input("https://raw.githubusercontent.com/agdamsbo/cognitive.index.lookup/main/data/sample.csv")
-read_input <- function(file, consider.na = c("NA", '""', "")) {
+read_input <- function(file, consider.na= c("NA", '""',"")){
+
   ext <- file_extension(file)
 
   tryCatch(
     {
       if (ext == "csv") {
-        df <- readr::read_csv(file = file, na = consider.na)
+        df <- readr::read_csv(file = file,na = consider.na)
       } else if (ext %in% c("xls", "xlsx")) {
         df <- openxlsx2::read_xlsx(file = file, na.strings = consider.na)
-      } else if (ext == "dta") {
+      } else if (ext == "dta"){
         df <- haven::read_dta(file = file)
       } else {
         stop("Input file format has to be either '.csv', '.xls' or '.xlsx'")

README.md

@@ -52,6 +52,3 @@ Install the latest version directly from GitHub:
 remotes::install_github("agdamsbo/REDCapCAST")
 ```
 
-## Code of Conduct
-
-Please note that the REDCapCAST project is released with a [Contributor Code of Conduct](https://agdamsbo.github.io/REDCapCAST/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.

data-raw/data-upload-examples.R

@@ -1,11 +1,9 @@
-mtcars_redcap <- mtcars |>
+mtcars_redcap <- mtcars |> dplyr::mutate(record_id=seq_len(dplyr::n()),
-  dplyr::mutate(
+                        name=rownames(mtcars)
-    record_id = seq_len(dplyr::n()),
+                        ) |>
-    name = rownames(mtcars)
+  dplyr::select(record_id,dplyr::everything())
-  ) |>
-  dplyr::select(record_id, dplyr::everything())
 
 mtcars_redcap |>
-  write.csv(here::here("data/mtcars_redcap.csv"), row.names = FALSE)
+  write.csv(here::here("data/mtcars_redcap.csv"),row.names = FALSE)
 
 usethis::use_data(mtcars_redcap, overwrite = TRUE)

data-raw/metadata_names.R

@@ -3,13 +3,12 @@
 #   "field_label", "select_choices_or_calculations", "field_note",
 #   "text_validation_type_or_show_slider_number", "text_validation_min",
 #   "text_validation_max", "identifier", "branching_logic", "required_field",
-#   "custom_alignment", "question_number", "matrix_group_name",
+#   "custom_alignment", "question_number", "matrix_group_name", "matrix_ranking",
-#   "matrix_ranking", "field_annotation"
+#   "field_annotation"
 # )
 
-metadata_names <- REDCapR::redcap_metadata_read(
+metadata_names <- REDCapR::redcap_metadata_read(redcap_uri = keyring::key_get("DB_URI"),
-  redcap_uri = keyring::key_get("DB_URI"),
+                                                 token = keyring::key_get("cast_api")
-  token = keyring::key_get("cast_api")
 )$data |> names()
 
 usethis::use_data(metadata_names, overwrite = TRUE, internal = TRUE)

data-raw/redcapcast_data.R

@@ -1,10 +1,9 @@
 ## code to prepare `redcapcast_data` dataset goes here
 
-redcapcast_data <- REDCapR::redcap_read(
+redcapcast_data <- REDCapR::redcap_read(redcap_uri = keyring::key_get("DB_URI"),
-  redcap_uri = keyring::key_get("DB_URI"),
+                                        token = keyring::key_get("cast_api"),
-  token = keyring::key_get("cast_api"),
+                                        raw_or_label = "label"
-  raw_or_label = "label"
+                                        )$data |> dplyr::tibble()
-)$data |> dplyr::tibble()
 
 # redcapcast_data <- easy_redcap(project.name = "redcapcast_pacakge",
 #                                uri = keyring::key_get("DB_URI"),

data-raw/redcapcast_meta.R

@@ -1,7 +1,6 @@
 ## code to prepare `redcapcast_meta` dataset goes here
-redcapcast_meta <- REDCapR::redcap_metadata_read(
+redcapcast_meta <- REDCapR::redcap_metadata_read(redcap_uri = keyring::key_get("DB_URI"),
-  redcap_uri = keyring::key_get("DB_URI"),
+                                          token = keyring::key_get("cast_api")
-  token = keyring::key_get("cast_api")
+                                          )$data
-)$data
 
 usethis::use_data(redcapcast_meta, overwrite = TRUE)

inst/WORDLIST

@@ -1,67 +0,0 @@
-Assesment
-CMD
-Codecov
-DOI
-DataDictionary
-GStat
-GithubActions
-JSON
-Lifecycle
-METACRAN
-POSIXct
-Pivotting
-README
-REDCap
-REDCapR
-REDCapRITS
-THe
-UI
-Whishes
-al
-api
-attr
-charater
-da
-dafault
-datetime
-demonstrational
-dmy
-doi
-dplyr
-ds
-dta
-et
-gues
-hms
-immprovements
-io
-jbi
-keyring
-labelled
-mRS
-matadata
-md
-mdy
-mtcars
-natively
-ncol
-og
-param
-pegeler
-perl
-pos
-readr
-rsconnect
-sel
-shinyapps
-stRoke
-stata
-strsplit
-thorugh
-tibble
-tidyverse
-transistion
-ui
-uri
-wil
-ymd

man/REDCap_split.Rd

@@ -50,19 +50,19 @@ library(RCurl)
 
 # Get the records
 records <- postForm(
-  uri = api_url, # Supply your site-specific URI
+  uri = api_url,     # Supply your site-specific URI
   token = api_token, # Supply your own API token
-  content = "record",
+  content = 'record',
-  format = "json",
+  format = 'json',
-  returnFormat = "json"
+  returnFormat = 'json'
 )
 
 # Get the metadata
 metadata <- postForm(
-  uri = api_url, # Supply your site-specific URI
+  uri = api_url,     # Supply your site-specific URI
   token = api_token, # Supply your own API token
-  content = "metadata",
+  content = 'metadata',
-  format = "json"
+  format = 'json'
 )
 
 # Convert exported JSON strings into a list of data.frames
@@ -75,8 +75,7 @@ records <- read.csv("/path/to/data/ExampleProject_DATA_2018-06-03_1700.csv")
 
 # Get the metadata
 metadata <- read.csv(
-  "/path/to/data/ExampleProject_DataDictionary_2018-06-03.csv"
+"/path/to/data/ExampleProject_DataDictionary_2018-06-03.csv")
-)
 
 # Split the tables
 REDCapRITS::REDCap_split(records, metadata)

man/ds2dd_detailed.Rd

@@ -44,8 +44,8 @@ data set (imported .dta file with `haven::read_dta()`. Default is "label"}
 
 \item{field.validation}{manually specify field validation(s). Vector of
 length 1 or ncol(data). Default is NULL and `levels()` are used for factors
-or attribute `factor.labels.attr` for haven_labelled data set (imported .dta
+or attribute `factor.labels.attr` for haven_labelled data set (imported .dta file with
-file with `haven::read_dta()`).}
+`haven::read_dta()`).}
 
 \item{metadata}{redcap metadata headings. Default is
 REDCapCAST:::metadata_names.}

man/guess_time_only_filter.Rd

@@ -32,7 +32,5 @@ has to be converted to character class before REDCap upload.
 \examples{
 data <- redcapcast_data
 data |> guess_time_only_filter()
-data |>
+data |> guess_time_only_filter(validate = TRUE) |> lapply(head)
-  guess_time_only_filter(validate = TRUE) |>
-  lapply(head)
 }

man/read_redcap_instrument.Rd

@@ -2,8 +2,7 @@
 % Please edit documentation in R/read_redcap_instrument.R
 \name{read_redcap_instrument}
 \alias{read_redcap_instrument}
-\title{Convenience function to download complete instrument, using token storage
+\title{Convenience function to download complete instrument, using token storage in keyring.}
-in keyring.}
 \usage{
 read_redcap_instrument(
   key,
@@ -25,13 +24,11 @@ read_redcap_instrument(
 
 \item{id_name}{id variable name. Default is "record_id".}
 
-\item{records}{specify the records to download. Index numbers.
+\item{records}{specify the records to download. Index numbers. Numeric vector.}
-Numeric vector.}
 }
 \value{
 data.frame
 }
 \description{
-Convenience function to download complete instrument, using token storage
+Convenience function to download complete instrument, using token storage in keyring.
-in keyring.
 }

man/redcap_wider.Rd

@@ -26,59 +26,35 @@ Handles longitudinal projects, but not yet repeated instruments.
 }
 \examples{
 # Longitudinal
-list1 <- list(
+list1 <- list(data.frame(record_id = c(1,2,1,2),
-  data.frame(
+redcap_event_name = c("baseline", "baseline", "followup", "followup"),
-    record_id = c(1, 2, 1, 2),
+age = c(25,26,27,28)),
-    redcap_event_name = c("baseline", "baseline", "followup", "followup"),
+data.frame(record_id = c(1,2),
-    age = c(25, 26, 27, 28)
+redcap_event_name = c("baseline", "baseline"),
-  ),
+gender = c("male", "female")))
-  data.frame(
-    record_id = c(1, 2),
-    redcap_event_name = c("baseline", "baseline"),
-    gender = c("male", "female")
-  )
-)
 redcap_wider(list1)
 # Simpel with two instruments
-list2 <- list(
+list2 <- list(data.frame(record_id = c(1,2),
-  data.frame(
+age = c(25,26)),
-    record_id = c(1, 2),
+data.frame(record_id = c(1,2),
-    age = c(25, 26)
+gender = c("male", "female")))
-  ),
-  data.frame(
-    record_id = c(1, 2),
-    gender = c("male", "female")
-  )
-)
 redcap_wider(list2)
 # Simple with single instrument
-list3 <- list(data.frame(
+list3 <- list(data.frame(record_id = c(1,2),
-  record_id = c(1, 2),
+age = c(25,26)))
-  age = c(25, 26)
-))
 redcap_wider(list3)
 # Longitudinal with repeatable instruments
-list4 <- list(
+list4 <- list(data.frame(record_id = c(1,2,1,2),
-  data.frame(
+redcap_event_name = c("baseline", "baseline", "followup", "followup"),
-    record_id = c(1, 2, 1, 2),
+age = c(25,26,27,28)),
-    redcap_event_name = c("baseline", "baseline", "followup", "followup"),
+data.frame(record_id = c(1,1,1,1,2,2,2,2),
-    age = c(25, 26, 27, 28)
+redcap_event_name = c("baseline", "baseline", "followup", "followup",
-  ),
+"baseline", "baseline", "followup", "followup"),
-  data.frame(
+redcap_repeat_instrument = "walk",
-    record_id = c(1, 1, 1, 1, 2, 2, 2, 2),
+redcap_repeat_instance=c(1,2,1,2,1,2,1,2),
-    redcap_event_name = c(
+dist = c(40, 32, 25, 33, 28, 24, 23, 36)),
-      "baseline", "baseline", "followup", "followup",
+data.frame(record_id = c(1,2),
-      "baseline", "baseline", "followup", "followup"
+redcap_event_name = c("baseline", "baseline"),
-    ),
+gender = c("male", "female")))
-    redcap_repeat_instrument = "walk",
-    redcap_repeat_instance = c(1, 2, 1, 2, 1, 2, 1, 2),
-    dist = c(40, 32, 25, 33, 28, 24, 23, 36)
-  ),
-  data.frame(
-    record_id = c(1, 2),
-    redcap_event_name = c("baseline", "baseline"),
-    gender = c("male", "female")
-  )
-)
 redcap_wider(list4)
 }

man/strsplitx.Rd

@@ -25,7 +25,6 @@ Can be used as a substitute of the base function. Main claim to fame is
 easing the split around the defined delimiter, see example.
 }
 \examples{
-test <- c("12 months follow-up", "3 steps", "mRS 6 weeks",
+test <- c("12 months follow-up", "3 steps", "mRS 6 weeks", "Counting to 231 now")
-"Counting to 231 now")
 strsplitx(test, "[0-9]", type = "around")
 }

man/time_only_correction.Rd

@@ -2,7 +2,8 @@
 % Please edit documentation in R/ds2dd_detailed.R
 \name{time_only_correction}
 \alias{time_only_correction}
-\title{Correction based on time_only_filter function}
+\title{Correction based on time_only_filter function. Introduces new class for easier
+validation labelling.}
 \usage{
 time_only_correction(data, ...)
 }
@@ -15,7 +16,8 @@ time_only_correction(data, ...)
 tibble
 }
 \description{
-Correction based on time_only_filter function
+Dependens on the data class "hms" introduced with
+`guess_time_only_filter()` and converts these
 }
 \examples{
 data <- redcapcast_data

renv.lock

@@ -39,17 +39,6 @@
       ],
       "Hash": "e76c401b631961c865b89bb5a4ea3b97"
     },
-    "Rcpp": {
-      "Package": "Rcpp",
-      "Version": "1.0.12",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "methods",
-        "utils"
-      ],
-      "Hash": "5ea2700d21e038ace58269ecdbeb9ec0"
-    },
     "askpass": {
       "Package": "askpass",
       "Version": "1.2.0",
@@ -80,16 +69,6 @@
       ],
       "Hash": "c39fbec8a30d23e721980b8afb31984c"
     },
-    "base64enc": {
-      "Package": "base64enc",
-      "Version": "0.1-3",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R"
-      ],
-      "Hash": "543776ae6848fde2f48ff3816d0628bc"
-    },
     "bit": {
       "Package": "bit",
       "Version": "4.0.5",
@@ -114,38 +93,6 @@
       ],
       "Hash": "9fe98599ca456d6552421db0d6772d8f"
     },
-    "bslib": {
-      "Package": "bslib",
-      "Version": "0.6.1",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "base64enc",
-        "cachem",
-        "grDevices",
-        "htmltools",
-        "jquerylib",
-        "jsonlite",
-        "lifecycle",
-        "memoise",
-        "mime",
-        "rlang",
-        "sass"
-      ],
-      "Hash": "c0d8599494bc7fb408cd206bbdd9cab0"
-    },
-    "cachem": {
-      "Package": "cachem",
-      "Version": "1.0.8",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "fastmap",
-        "rlang"
-      ],
-      "Hash": "c35768291560ce302c0a6589f92e837d"
-    },
     "checkmate": {
       "Package": "checkmate",
       "Version": "2.3.1",
@@ -179,13 +126,6 @@
       ],
       "Hash": "3f038e5ac7f41d4ac41ce658c85e3042"
     },
-    "commonmark": {
-      "Package": "commonmark",
-      "Version": "1.9.1",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Hash": "5d8225445acb167abf7797de48b2ee3c"
-    },
     "cpp11": {
       "Package": "cpp11",
       "Version": "0.4.7",
@@ -218,17 +158,6 @@
       ],
       "Hash": "ce88d13c0b10fe88a37d9c59dba2d7f9"
     },
-    "digest": {
-      "Package": "digest",
-      "Version": "0.6.34",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "utils"
-      ],
-      "Hash": "7ede2ee9ea8d3edbf1ca84c1e333ad1a"
-    },
     "dplyr": {
       "Package": "dplyr",
       "Version": "1.1.4",
@@ -252,17 +181,6 @@
       ],
       "Hash": "fedd9d00c2944ff00a0e2696ccf048ec"
     },
-    "ellipsis": {
-      "Package": "ellipsis",
-      "Version": "0.3.2",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "rlang"
-      ],
-      "Hash": "bb0eec2fe32e88d9e2836c2f73ea2077"
-    },
     "fansi": {
       "Package": "fansi",
       "Version": "1.0.6",
@@ -275,13 +193,6 @@
       ],
       "Hash": "962174cf2aeb5b9eea581522286a911f"
     },
-    "fastmap": {
-      "Package": "fastmap",
-      "Version": "1.1.1",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Hash": "f7736a18de97dea803bde0a2daaafb27"
-    },
     "filelock": {
       "Package": "filelock",
       "Version": "1.0.3",
@@ -292,45 +203,6 @@
       ],
       "Hash": "192053c276525c8495ccfd523aa8f2d1"
     },
-    "fontawesome": {
-      "Package": "fontawesome",
-      "Version": "0.5.2",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "htmltools",
-        "rlang"
-      ],
-      "Hash": "c2efdd5f0bcd1ea861c2d4e2a883a67d"
-    },
-    "forcats": {
-      "Package": "forcats",
-      "Version": "1.0.0",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "cli",
-        "glue",
-        "lifecycle",
-        "magrittr",
-        "rlang",
-        "tibble"
-      ],
-      "Hash": "1a0a9a3d5083d0d573c4214576f1e690"
-    },
-    "fs": {
-      "Package": "fs",
-      "Version": "1.6.3",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "methods"
-      ],
-      "Hash": "47b5f30c720c23999b913a1a635cf0bb"
-    },
     "generics": {
       "Package": "generics",
       "Version": "0.1.3",
@@ -353,27 +225,6 @@
       ],
       "Hash": "e0b3a53876554bd45879e596cdb10a52"
     },
-    "haven": {
-      "Package": "haven",
-      "Version": "2.5.4",
-      "Source": "Repository",
-      "Repository": "RSPM",
-      "Requirements": [
-        "R",
-        "cli",
-        "cpp11",
-        "forcats",
-        "hms",
-        "lifecycle",
-        "methods",
-        "readr",
-        "rlang",
-        "tibble",
-        "tidyselect",
-        "vctrs"
-      ],
-      "Hash": "9171f898db9d9c4c1b2c745adc2c1ef1"
-    },
     "hms": {
       "Package": "hms",
       "Version": "1.1.3",
@@ -388,38 +239,6 @@
       ],
       "Hash": "b59377caa7ed00fa41808342002138f9"
     },
-    "htmltools": {
-      "Package": "htmltools",
-      "Version": "0.5.7",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "base64enc",
-        "digest",
-        "ellipsis",
-        "fastmap",
-        "grDevices",
-        "rlang",
-        "utils"
-      ],
-      "Hash": "2d7b3857980e0e0d0a1fd6f11928ab0f"
-    },
-    "httpuv": {
-      "Package": "httpuv",
-      "Version": "1.6.14",
-      "Source": "Repository",
-      "Repository": "RSPM",
-      "Requirements": [
-        "R",
-        "R6",
-        "Rcpp",
-        "later",
-        "promises",
-        "utils"
-      ],
-      "Hash": "16abeb167dbf511f8cc0552efaf05bab"
-    },
     "httr": {
       "Package": "httr",
       "Version": "1.4.7",
@@ -435,16 +254,6 @@
       ],
       "Hash": "ac107251d9d9fd72f0ca8049988f1d7f"
     },
-    "jquerylib": {
-      "Package": "jquerylib",
-      "Version": "0.1.4",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "htmltools"
-      ],
-      "Hash": "5aab57a3bd297eee1c1d862735972182"
-    },
     "jsonlite": {
       "Package": "jsonlite",
       "Version": "1.8.8",
@@ -475,17 +284,6 @@
       ],
       "Hash": "5cd8cfb2e90c57110b7dd1785c599aba"
     },
-    "later": {
-      "Package": "later",
-      "Version": "1.3.2",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "Rcpp",
-        "rlang"
-      ],
-      "Hash": "a3e051d405326b8b0012377434c62b37"
-    },
     "lifecycle": {
       "Package": "lifecycle",
       "Version": "1.0.4",
@@ -509,17 +307,6 @@
       ],
       "Hash": "7ce2733a9826b3aeb1775d56fd305472"
     },
-    "memoise": {
-      "Package": "memoise",
-      "Version": "2.0.1",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "cachem",
-        "rlang"
-      ],
-      "Hash": "e2817ccf4a065c5d9d7f2cfbe7c1d78c"
-    },
     "mime": {
       "Package": "mime",
       "Version": "0.12",
@@ -540,35 +327,6 @@
       ],
       "Hash": "2a0dc8c6adfb6f032e4d4af82d258ab5"
     },
-    "openxlsx2": {
-      "Package": "openxlsx2",
-      "Version": "1.4",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "R6",
-        "Rcpp",
-        "grDevices",
-        "magrittr",
-        "stringi",
-        "utils",
-        "zip"
-      ],
-      "Hash": "9fa7cdc5fbdb1c8511fdde72a944db63"
-    },
-    "packrat": {
-      "Package": "packrat",
-      "Version": "0.9.2",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "tools",
-        "utils"
-      ],
-      "Hash": "55ddd2d4a1959535f18393478b0c14a6"
-    },
     "pillar": {
       "Package": "pillar",
       "Version": "1.9.0",
@@ -620,22 +378,6 @@
       ],
       "Hash": "f4625e061cb2865f111b47ff163a5ca6"
     },
-    "promises": {
-      "Package": "promises",
-      "Version": "1.2.1",
-      "Source": "Repository",
-      "Repository": "RSPM",
-      "Requirements": [
-        "R6",
-        "Rcpp",
-        "fastmap",
-        "later",
-        "magrittr",
-        "rlang",
-        "stats"
-      ],
-      "Hash": "0d8a15c9d000970ada1ab21405387dee"
-    },
     "purrr": {
       "Package": "purrr",
       "Version": "1.0.2",
@@ -705,83 +447,6 @@
       ],
       "Hash": "42548638fae05fd9a9b5f3f437fbbbe2"
     },
-    "rsconnect": {
-      "Package": "rsconnect",
-      "Version": "1.2.1",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "cli",
-        "curl",
-        "digest",
-        "jsonlite",
-        "lifecycle",
-        "openssl",
-        "packrat",
-        "renv",
-        "rlang",
-        "rstudioapi",
-        "tools",
-        "yaml"
-      ],
-      "Hash": "94bb3a2125b01b13dd2e4a784c2a9639"
-    },
-    "rstudioapi": {
-      "Package": "rstudioapi",
-      "Version": "0.15.0",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Hash": "5564500e25cffad9e22244ced1379887"
-    },
-    "sass": {
-      "Package": "sass",
-      "Version": "0.4.8",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R6",
-        "fs",
-        "htmltools",
-        "rappdirs",
-        "rlang"
-      ],
-      "Hash": "168f9353c76d4c4b0a0bbf72e2c2d035"
-    },
-    "shiny": {
-      "Package": "shiny",
-      "Version": "1.8.0",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "R6",
-        "bslib",
-        "cachem",
-        "commonmark",
-        "crayon",
-        "ellipsis",
-        "fastmap",
-        "fontawesome",
-        "glue",
-        "grDevices",
-        "htmltools",
-        "httpuv",
-        "jsonlite",
-        "later",
-        "lifecycle",
-        "methods",
-        "mime",
-        "promises",
-        "rlang",
-        "sourcetools",
-        "tools",
-        "utils",
-        "withr",
-        "xtable"
-      ],
-      "Hash": "3a1f41807d648a908e3c7f0334bf85e6"
-    },
     "sodium": {
       "Package": "sodium",
       "Version": "1.3.1",
@@ -789,16 +454,6 @@
       "Repository": "CRAN",
       "Hash": "dd86d6fd2a01d4eb3777dfdee7076d56"
     },
-    "sourcetools": {
-      "Package": "sourcetools",
-      "Version": "0.1.7-1",
-      "Source": "Repository",
-      "Repository": "RSPM",
-      "Requirements": [
-        "R"
-      ],
-      "Hash": "5f5a7629f956619d519205ec475fe647"
-    },
     "stringi": {
       "Package": "stringi",
       "Version": "1.8.3",
@@ -967,31 +622,12 @@
       ],
       "Hash": "d31b6c62c10dcf11ec530ca6b0dd5d35"
     },
-    "xtable": {
-      "Package": "xtable",
-      "Version": "1.8-4",
-      "Source": "Repository",
-      "Repository": "CRAN",
-      "Requirements": [
-        "R",
-        "stats",
-        "utils"
-      ],
-      "Hash": "b8acdf8af494d9ec19ccb2481a9b11c2"
-    },
     "yaml": {
       "Package": "yaml",
       "Version": "2.3.8",
       "Source": "Repository",
       "Repository": "CRAN",
       "Hash": "29240487a071f535f5e5d5a323b7afbd"
-    },
-    "zip": {
-      "Package": "zip",
-      "Version": "2.3.1",
-      "Source": "Repository",
-      "Repository": "RSPM",
-      "Hash": "fcc4bd8e6da2d2011eb64a5e5cc685ab"
     }
   }
 }

tests/spelling.R

@@ -1,3 +0,0 @@
-if(requireNamespace('spelling', quietly = TRUE))
-  spelling::spell_check_test(vignettes = TRUE, error = FALSE,
-                             skip_on_cran = TRUE)

tests/testthat/data/create-ref-data.R

@@ -7,23 +7,22 @@ library(magrittr)
 library(jsonlite)
 
 
-ref_data_location <- function(x) file.path("tests", "testthat", "data", x)
+ref_data_location <- function(x) file.path("tests","testthat","data", x)
 
 # RCurl -------------------------------------------------------------------
 
 REDCap_split(
-  ref_data_location("ExampleProject_records.json") %>% fromJSON(),
+  ref_data_location("ExampleProject_records.json") %>% fromJSON,
-  ref_data_location("ExampleProject_metadata.json") %>% fromJSON()
+  ref_data_location("ExampleProject_metadata.json") %>% fromJSON
-) %>% digest()
+  ) %>% digest
 
 
 # Basic CSV ---------------------------------------------------------------
 
 REDCap_split(
-  ref_data_location("ExampleProject_DATA_2018-06-07_1129.csv") %>% read.csv(),
+  ref_data_location("ExampleProject_DATA_2018-06-07_1129.csv") %>% read.csv,
-  ref_data_location("ExampleProject_DataDictionary_2018-06-07.csv") %>%
+  ref_data_location("ExampleProject_DataDictionary_2018-06-07.csv") %>% read.csv
-    read.csv()
+  ) %>% digest
-) %>% digest()
 
 # REDCap R Export ---------------------------------------------------------
 
@@ -31,11 +30,10 @@ source("tests/testthat/helper-ExampleProject_R_2018-06-07_1129.r")
 
 REDCap_split(
   ref_data_location("ExampleProject_DATA_2018-06-07_1129.csv") %>%
-    read.csv() %>%
+    read.csv %>%
-    REDCap_process_csv(),
+    REDCap_process_csv,
-  ref_data_location("ExampleProject_DataDictionary_2018-06-07.csv") %>%
+  ref_data_location("ExampleProject_DataDictionary_2018-06-07.csv") %>% read.csv
-    read.csv()
+  ) %>% digest
-) %>% digest()
 
 # Longitudinal data from @pbchase; Issue #7 -------------------------------
 
@@ -43,10 +41,9 @@ file_paths <- vapply(
   c(
     records = "WARRIORtestForSoftwa_DATA_2018-06-21_1431.csv",
     metadata = "WARRIORtestForSoftwareUpgrades_DataDictionary_2018-06-21.csv"
-  ),
+  ), FUN.VALUE = "character", ref_data_location
-  FUN.VALUE = "character", ref_data_location
 )
 
 redcap <- lapply(file_paths, read.csv, stringsAsFactors = FALSE)
-redcap[["metadata"]] <- with(redcap, metadata[metadata[, 1] > "", ])
+redcap[["metadata"]] <- with(redcap, metadata[metadata[,1] > "",])
-with(redcap, REDCap_split(records, metadata)) %>% digest()
+with(redcap, REDCap_split(records, metadata)) %>% digest

tests/testthat/helper-ExampleProject_R_2018-06-07_1129.r

@@ -1,5 +1,5 @@
 REDCap_process_csv <- function(data) {
-  # Load Hmisc library
+  #Load Hmisc library
   if (!requireNamespace("Hmisc", quietly = TRUE)) {
     stop("This test requires the 'Hmisc' package")
   }
@@ -36,13 +36,13 @@ REDCap_process_csv <- function(data) {
   Hmisc::label(data$color) <- "Color"
   Hmisc::label(data$customer) <- "Customer Name"
   Hmisc::label(data$sale_complete) <- "Complete?"
-  # Setting Units
+  #Setting Units
 
 
-  # Setting Factors(will create new variable for factors)
+  #Setting Factors(will create new variable for factors)
   data$redcap_repeat_instrument.factor <-
     factor(data$redcap_repeat_instrument, levels <-
-      c("sale"))
+             c("sale"))
   data$cyl.factor <-
     factor(data$cyl, levels <- c("3", "4", "5", "6", "7", "8"))
   data$vs.factor <- factor(data$vs, levels <- c("1", "0"))
@@ -50,36 +50,36 @@ REDCap_process_csv <- function(data) {
   data$gear.factor <- factor(data$gear, levels <- c("3", "4", "5"))
   data$carb.factor <-
     factor(data$carb, levels <-
-      c("1", "2", "3", "4", "5", "6", "7", "8"))
+             c("1", "2", "3", "4", "5", "6", "7", "8"))
   data$color_available___red.factor <-
     factor(data$color_available___red, levels <-
-      c("0", "1"))
+             c("0", "1"))
   data$color_available___green.factor <-
     factor(data$color_available___green, levels <-
-      c("0", "1"))
+             c("0", "1"))
   data$color_available___blue.factor <-
     factor(data$color_available___blue, levels <-
-      c("0", "1"))
+             c("0", "1"))
   data$color_available___black.factor <-
     factor(data$color_available___black, levels <-
-      c("0", "1"))
+             c("0", "1"))
   data$motor_trend_cars_complete.factor <-
     factor(data$motor_trend_cars_complete, levels <-
-      c("0", "1", "2"))
+             c("0", "1", "2"))
   data$letter_group___a.factor <-
     factor(data$letter_group___a, levels <-
-      c("0", "1"))
+             c("0", "1"))
   data$letter_group___b.factor <-
     factor(data$letter_group___b, levels <-
-      c("0", "1"))
+             c("0", "1"))
   data$letter_group___c.factor <-
     factor(data$letter_group___c, levels <-
-      c("0", "1"))
+             c("0", "1"))
   data$choice.factor <-
     factor(data$choice, levels <- c("choice1", "choice2"))
   data$grouping_complete.factor <-
     factor(data$grouping_complete, levels <-
-      c("0", "1", "2"))
+             c("0", "1", "2"))
   data$color.factor <-
     factor(data$color, levels <- c("1", "2", "3", "4"))
   data$sale_complete.factor <-

tests/testthat/test-csv-exports.R

@@ -1,3 +1,5 @@
+
+
 # Set up the path and data -------------------------------------------------
 metadata <- read.csv(
   get_data_location("ExampleProject_DataDictionary_2018-06-07.csv"),
@@ -6,8 +8,7 @@ metadata <- read.csv(
 
 records <-
   read.csv(get_data_location("ExampleProject_DATA_2018-06-07_1129.csv"),
-    stringsAsFactors = TRUE
+           stringsAsFactors = TRUE)
-  )
 
 redcap_output_csv1 <- REDCap_split(records, metadata)
 
@@ -18,21 +19,20 @@ test_that("CSV export matches reference", {
 
 # Test that REDCap_split can handle a focused dataset
 
-records_red <- records[
+records_red <- records[!records$redcap_repeat_instrument == "sale",
-  !records$redcap_repeat_instrument == "sale",
+                       !names(records) %in%
-  !names(records) %in%
+                         metadata$field_name[metadata$form_name == "sale"] &
-    metadata$field_name[metadata$form_name == "sale"] &
+                         !names(records) == "sale_complete"]
-    !names(records) == "sale_complete"
-]
 records_red$redcap_repeat_instrument <-
   as.character(records_red$redcap_repeat_instrument)
 
 redcap_output_red <- REDCap_split(records_red, metadata)
 
 
-test_that("REDCap_split handles subset dataset", {
+test_that("REDCap_split handles subset dataset",
-  testthat::expect_length(redcap_output_red, 1)
+          {
-})
+            testthat::expect_length(redcap_output_red, 1)
+          })
 
 
 # Test that R code enhanced CSV export matches reference --------------------
@@ -47,40 +47,35 @@ if (requireNamespace("Hmisc", quietly = TRUE)) {
 
 
 if (requireNamespace("readr", quietly = TRUE)) {
+
   metadata <-
     readr::read_csv(get_data_location(
-      "ExampleProject_DataDictionary_2018-06-07.csv"
+      "ExampleProject_DataDictionary_2018-06-07.csv"))
-    ))
 
   records <-
     readr::read_csv(get_data_location(
-      "ExampleProject_DATA_2018-06-07_1129.csv"
+      "ExampleProject_DATA_2018-06-07_1129.csv"))
-    ))
 
   redcap_output_readr <- REDCap_split(records, metadata)
 
   expect_matching_elements <- function(FUN) {
     FUN <- match.fun(FUN)
-    expect_identical(
+    expect_identical(lapply(redcap_output_readr, FUN),
-      lapply(redcap_output_readr, FUN),
+                     lapply(redcap_output_csv1, FUN))
-      lapply(redcap_output_csv1, FUN)
-    )
   }
 
   test_that("Result of data read in with `readr` will
-            match result with `read.csv`", {
+            match result with `read.csv`",
-    # The list itself
+            {
-    expect_identical(
+              # The list itself
-      length(redcap_output_readr),
+              expect_identical(length(redcap_output_readr),
-      length(redcap_output_csv1)
+                               length(redcap_output_csv1))
-    )
+              expect_identical(names(redcap_output_readr),
-    expect_identical(
+                               names(redcap_output_csv1))
-      names(redcap_output_readr),
+
-      names(redcap_output_csv1)
+              # Each element of the list
-    )
+              expect_matching_elements(names)
+              expect_matching_elements(dim)
+            })
 
-    # Each element of the list
-    expect_matching_elements(names)
-    expect_matching_elements(dim)
-  })
 }

tests/testthat/test-utils.R

@@ -1,22 +1,20 @@
 test_that("strsplitx works", {
   expect_equal(2 * 2, 4)
-  test <- c("12 months follow-up", "3 steps", "mRS 6 weeks",
+  test <- c("12 months follow-up", "3 steps", "mRS 6 weeks", "Counting to 231 now")
-            "Counting to 231 now")
+  expect_length(strsplitx(test,"[0-9]",type="around")[[1]],3)
-  expect_length(strsplitx(test, "[0-9]", type = "around")[[1]], 3)
 
-  expect_equal(strsplitx(test, "[0-9]", type = "classic")[[2]][1], "")
+  expect_equal(strsplitx(test,"[0-9]",type="classic")[[2]][1],"")
-  expect_length(strsplitx(test, "[0-9]", type = "classic")[[4]], 4)
+  expect_length(strsplitx(test,"[0-9]",type="classic")[[4]],4)
 
-  expect_length(strsplitx(test, "[0-9]", type = "classic")[[4]], 4)
+  expect_length(strsplitx(test,"[0-9]",type="classic")[[4]],4)
 })
 
 test_that("d2w works", {
-  expect_length(d2w(c(2:8, 21)), 8)
 
-  expect_equal(d2w(data.frame(2:7, 3:8, 1),
+  expect_length(d2w(c(2:8,21)),8)
-    lang = "da",
-    neutrum = TRUE
-  )[1, 3], "et")
 
-  expect_equal(d2w(list(2:8, c(2, 6, 4, 23), 2), everything = T)[[2]][4], "two three")
+  expect_equal(d2w(data.frame(2:7,3:8,1),lang="da",
+                              neutrum=TRUE)[1,3],"et")
+
+  expect_equal(d2w(list(2:8,c(2,6,4,23),2), everything=T)[[2]][4],"two three")
 })

vignettes/Database-creation.Rmd

@@ -25,8 +25,7 @@ THe first iteration of a dataset to data dictionary function is the `ds2dd()`, w
 ```{r eval=FALSE}
 mtcars |>
   dplyr::mutate(record_id = seq_len(dplyr::n())) |>
-  ds2dd() |>
+  ds2dd() |> str()
-  str()
 ```
 
 The more advanced `ds2dd_detailed()` is a natural development. It will try to apply the most common data classes for data validation and will assume that the first column is the id number. It outputs a list with the dataset with modified variable names to comply with REDCap naming conventions and a data dictionary. 
@@ -38,8 +37,7 @@ dd_ls <- mtcars |>
   dplyr::mutate(record_id = seq_len(dplyr::n())) |>
   dplyr::select(record_id, dplyr::everything()) |>
   ds2dd_detailed()
-dd_ls |> 
+dd_ls |> str()
-  str()
 ```
 
 Additional specifications to the DataDictionary can be made manually, or it can be uploaded and modified manually in the graphical user interface on the web page.

vignettes/Introduction.Rmd

@@ -33,23 +33,17 @@ redcapcast_meta |> gt::gt()
 ```
 ```{r}
 list <-
-  REDCap_split(
+  REDCap_split(records = redcapcast_data,
-    records = redcapcast_data,
+                           metadata = redcapcast_meta,
-    metadata = redcapcast_meta,
+                           forms = "repeating")|> sanitize_split()
-    forms = "repeating"
-  ) |> 
-  sanitize_split()
 str(list)
 ```
 
 ```{r}
 list <-
-  REDCap_split(
+  REDCap_split(records = redcapcast_data,
-    records = redcapcast_data,
+                           metadata = redcapcast_meta,
-    metadata = redcapcast_meta,
+                           forms = "all") |> sanitize_split()
-    forms = "all"
-  ) |> 
-  sanitize_split()
 str(list)
 ```
 
@@ -68,3 +62,5 @@ The function works very similar to the `REDCapR::redcap_read()` in allowing to s
 ```{r}
 redcap_wider(list) |> str()
 ```
+
+