DESCRIPTION

@@ -1,6 +1,6 @@
 Package: REDCapCAST
 Title: REDCap Castellated Data Handling
-Version: 24.1.2
+Version: 24.1.1
 Authors@R: c(
     person("Andreas Gammelgaard", "Damsbo", email = "agdamsbo@clin.au.dk", 
     role = c("aut", "cre"),comment = c(ORCID = "0000-0002-7559-1154")), 
@@ -27,13 +27,12 @@ Suggests:
     jsonlite,
     testthat,
     Hmisc,
+    readr,
     knitr,
     rmarkdown,
     gt,
     usethis,
-    ggplot2,
+    ggplot2
-    haven,
-    here
 License: GPL (>= 3)
 Encoding: UTF-8
 LazyData: true
@@ -46,15 +45,12 @@ Imports:
     tidyr,
     tidyselect,
     keyring,
-    purrr,
+    purrr
-    readr,
-    stats
 Collate: 
     'utils.r'
     'process_user_input.r'
     'REDCap_split.r'
     'ds2dd.R'
-    'ds2dd_detailed.R'
     'easy_redcap.R'
     'read_redcap_tables.R'
     'redcap_wider.R'

NAMESPACE

@@ -4,11 +4,9 @@ export(REDCap_split)
 export(clean_redcap_name)
 export(d2w)
 export(ds2dd)
-export(ds2dd_detailed)
 export(easy_redcap)
 export(focused_metadata)
 export(get_api_key)
-export(guess_time_only_filter)
 export(match_fields_to_form)
 export(read_redcap_tables)
 export(redcap_wider)
@@ -23,6 +21,5 @@ importFrom(keyring,key_get)
 importFrom(keyring,key_list)
 importFrom(keyring,key_set)
 importFrom(purrr,reduce)
-importFrom(readr,parse_time)
 importFrom(tidyr,pivot_wider)
 importFrom(tidyselect,all_of)

NEWS.md

@@ -1,15 +1,3 @@
-# REDCapCAST 24.1.2
-
-### Functions
-
-* Fix: `ds2dd()`: uses correct default dd column names. Will be deprecated.
-
-* NEW: `ds2dd_detailed()`: extension of the `ds2dd()`, which serves to preserve as much metadata as possible automatically. Depends on a group of helper functions also introduced. Of special note is the `guess_time_only_filter()`, which will try to guess which columns/variables should be formatted as time only formats. Supports hms time format. DETAILED INSTRUCTION AND VIGNETTE IS PENDING.
-
-### Other
-
-I believe `renv` has now been added and runs correctly. After clone, do `renv::restore()` to install all necessary package to modify the package.
-
 # REDCapCAST 24.1.1
 
 ### Functions

R/ds2dd.R

@@ -1,13 +1,8 @@
-utils::globalVariables(c("metadata_names"))
+utils::globalVariables(c("redcapcast_meta"))
-#' (DEPRECATED) Data set to data dictionary function
+#' Data set to data dictionary function
 #'
-#' @description
-#' Creates a very basic data dictionary skeleton. Please see `ds2dd_detailed()`
-#' for a more advanced function.
-#'
-#' @details
 #' Migrated from stRoke ds2dd(). Fits better with the functionality of
-#' 'REDCapCAST'.
+#' 'REDCapCAST'
 #' @param ds data set
 #' @param record.id name or column number of id variable, moved to first row of
 #' data dictionary, character of integer. Default is "record_id".
@@ -21,7 +16,7 @@ utils::globalVariables(c("metadata_names"))
 #' @param include.column.names Flag to give detailed output including new
 #' column names for original data set for upload.
 #' @param metadata Metadata column names. Default is the included
-#' REDCapCAST::metadata_names.
+#' REDCapCAST::redcapcast_data.
 #'
 #' @return data.frame or list of data.frame and vector
 #' @export

R/ds2dd_detailed.R

@@ -1,343 +0,0 @@
-utils::globalVariables(c(  "stats::setNames",  "field_name",  "field_type",  "select_choices_or_calculations"))
-#' Try at determining which are true time only variables
-#'
-#' @description
-#' This is just a try at guessing data type based on data class and column names
-#' hoping for a tiny bit of naming consistency. R does not include a time-only
-#' data format natively, so the "hms" class from `readr` is used. This
-#' has to be converted to character class before REDCap upload.
-#'
-#' @param data data set
-#' @param validate flag to output validation data. Will output list.
-#' @param sel.pos Positive selection regex string
-#' @param sel.neg Negative selection regex string
-#'
-#' @return character vector or list depending on `validate` flag.
-#' @export
-#'
-#' @examples
-#' data <- redcapcast_data
-#' data |> guess_time_only_filter()
-#' data |> guess_time_only_filter(validate = TRUE) |> 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))) |>
-    (\(x) names(data)[do.call(c, x)])()
-
-  time_only_log <- datetime_nms |> (\(x) {
-    ## Detects which are determined true Time only variables
-    ## Inspection is necessary
-    grepl(pattern = sel.pos, x = x) &
-      !grepl(pattern = sel.neg, x = x)
-  })()
-
-  if (validate) {
-    list(
-      "is.POSIX" = data[datetime_nms],
-      "is.datetime" = data[datetime_nms[!time_only_log]],
-      "is.time_only" = data[datetime_nms[time_only_log]]
-    )
-  } else {
-    datetime_nms[time_only_log]
-  }
-}
-
-#' 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()`
-#'
-#' @return tibble
-#' @importFrom readr parse_time
-#'
-#' @examples
-#' data <- redcapcast_data
-#' ## data |> time_only_correction()
-time_only_correction <- function(data, ...) {
-  nms <- guess_time_only_filter(data, ...)
-  z <- nms |>
-    lapply(\(y) {
-      readr::parse_time(format(data[[y]], format = "%H:%M:%S"))
-    }) |>
-    suppressMessages(dplyr::bind_cols()) |>
-    stats::setNames(nm = nms)
-  data[nms] <- z
-  data
-}
-
-#' Change "hms" to "character" for REDCap upload.
-#'
-#' @param data data set
-#'
-#' @return data.frame or tibble
-#'
-#' @examples
-#' data <- redcapcast_data
-#' ## data |> time_only_correction() |> hms2character()
-hms2character <- function(data) {
-  data |>
-    lapply(function(x) {
-      if ("hms" %in% class(x)) {
-        as.character(x)
-      } else {
-        x
-      }
-    }) |>
-    dplyr::bind_cols()
-}
-
-#' Extract data from stata file for data dictionary
-#'
-#' @details
-#' This function is a natural development of the ds2dd() function. It assumes
-#' that the first column is the ID-column. No checks.
-#' Please, do always inspect the data dictionary before upload.
-#'
-#' Ensure, that the data set is formatted with as much information as possible.
-#'
-#' `field.type` can be supplied
-#'
-#' @param data data frame
-#' @param date.format date format, character string. ymd/dmy/mdy. dafault is
-#' dmy.
-#' @param add.auto.id flag to add id column
-#' @param form.name manually specify form name(s). Vector of length 1 or
-#' ncol(data). Default is NULL and "data" is used.
-#' @param field.type manually specify field type(s). Vector of length 1 or
-#' ncol(data). Default is NULL and "text" is used for everything but factors,
-#' which wil get "radio".
-#' @param field.label manually specify field label(s). Vector of length 1 or
-#' ncol(data). Default is NULL and colnames(data) is used or attribute
-#' `field.label.attr` for haven_labelled data set (imported .dta file with
-#' `haven::read_dta()`).
-#' @param field.label.attr attribute name for named labels for haven_labelled
-#' 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 file with
-#' `haven::read_dta()`).
-#' @param metadata redcap metadata headings. Default is
-#' REDCapCAST:::metadata_names.
-#' @param validate.time Flag to validate guessed time columns
-#' @param time.var.sel.pos Positive selection regex string passed to
-#' `gues_time_only_filter()` as sel.pos.
-#' @param time.var.sel.neg Negative selection regex string passed to
-#' `gues_time_only_filter()` as sel.neg.
-#'
-#' @return list of length 2
-#' @export
-#'
-#' @examples
-#' data <- redcapcast_data
-#' data |> ds2dd_detailed(validate.time = TRUE)
-#' data |> ds2dd_detailed()
-#' iris |> ds2dd_detailed(add.auto.id = TRUE)
-#' mtcars |> ds2dd_detailed(add.auto.id = TRUE)
-ds2dd_detailed <- function(data,
-                           add.auto.id = FALSE,
-                           date.format = "dmy",
-                           form.name = NULL,
-                           field.type = NULL,
-                           field.label = NULL,
-                           field.label.attr ="label",
-                           field.validation = NULL,
-                           metadata = metadata_names,
-                           validate.time = FALSE,
-                           time.var.sel.pos = "[Tt]i[d(me)]",
-                           time.var.sel.neg = "[Dd]at[eo]") {
-  ## Handles the odd case of no id column present
-  if (add.auto.id) {
-    data <- dplyr::tibble(
-      default_trial_id = seq_len(nrow(data)),
-      data
-    )
-    message("A default id column has been added")
-  }
-
-  if (validate.time) {
-    return(data |> guess_time_only_filter(validate = TRUE))
-  }
-
-  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 will be treated as such.")
-    data.source <- "dta"
-  } else {
-    data.source <- ""
-  }
-
-  ## data classes
-
-  ### Only keeps the first class, as time fields (POSIXct/POSIXt) has two classes
-  if (data.source == "dta") {
-    data_classes <-
-      data |>
-      haven::as_factor() |>
-      time_only_correction(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(sel.pos = time.var.sel.pos, sel.neg = time.var.sel.neg) |>
-      lapply(\(x)class(x)[1]) |>
-      (\(x)do.call(c, x))()
-  }
-
-  ## ---------------------------------------
-  ## Building the data dictionary
-  ## ---------------------------------------
-
-  ## skeleton
-
-  dd <- data.frame(matrix(ncol = length(metadata), nrow = ncol(data))) |>
-    stats::setNames(metadata) |>
-    dplyr::tibble()
-
-  dd$field_name <- gsub(" ", "_", tolower(colnames(data)))
-
-  ## form_name
-  if (is.null(form.name)) {
-    dd$form_name <- "data"
-  } else {
-    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).")
-    }
-  }
-
-  ## field_label
-
-  if (is.null(field.label)) {
-    if (data.source == "dta") {
-      label <- data |>
-        lapply(function(x) {
-          if (haven::is.labelled(x)) {
-            attributes(x)[[field.label.attr]]
-          } else {
-            NA
-          }
-        }) |>
-        (\(x)do.call(c, x))()
-    } else {
-      label <- data |> colnames()
-    }
-
-    dd <-
-      dd |> dplyr::mutate(field_label = dplyr::if_else(is.na(label), field_name, label))
-  } else {
-    if (length(field.label) == 1 | length(field.label) == nrow(dd)) {
-      dd$field_label <- field.label
-    } else {
-      stop("Length of supplied 'field.label' has to be one (1) or ncol(data).")
-    }
-  }
-
-
-  ## field_type
-
-  if (is.null(field.type)) {
-    dd$field_type <- "text"
-
-    dd <-
-      dd |> dplyr::mutate(field_type = dplyr::if_else(data_classes == "factor", "radio", field_type))
-  } else {
-    if (length(field.type) == 1 | length(field.type) == nrow(dd)) {
-      dd$field_type <- field.type
-    } else {
-      stop("Length of supplied 'field.type' has to be one (1) or ncol(data).")
-    }
-  }
-
-  ## validation
-
-  if (is.null(field.validation)) {
-    dd <-
-      dd |> dplyr::mutate(
-        text_validation_type_or_show_slider_number = dplyr::case_when(
-          data_classes == "Date" ~ paste0("date_", date.format),
-          data_classes ==
-            "hms" ~ "time_hh_mm_ss",
-          ## Self invented format after filtering
-          data_classes ==
-            "POSIXct" ~ paste0("datetime_", date.format),
-          data_classes ==
-            "numeric" ~ "number"
-        )
-      )
-  } else {
-    if (length(field.validation) == 1 | length(field.validation) == nrow(dd)) {
-      dd$text_validation_type_or_show_slider_number <- field.validation
-    } else {
-      stop("Length of supplied 'field.validation' has to be one (1) or ncol(data).")
-    }
-  }
-
-
-
-  ## choices
-
-  if (data.source == "dta") {
-    factor_levels <- data |>
-      lapply(function(x) {
-        if (haven::is.labelled(x)) {
-          att <- attributes(x)$labels
-          paste(paste(att, names(att), sep = ", "), collapse = " | ")
-        } else {
-          NA
-        }
-      }) |>
-      (\(x)do.call(c, x))()
-  } else {
-    factor_levels <- data |>
-      lapply(function(x) {
-        if (is.factor(x)) {
-          ## Re-factors to avoid confusion with missing levels
-          ## Assumes alle relevant levels are represented in the data
-          re_fac <- factor(x)
-          paste(paste(unique(as.numeric(re_fac)), levels(re_fac), sep = ", "), collapse = " | ")
-        } else {
-          NA
-        }
-      }) |>
-      (\(x)do.call(c, x))()
-  }
-
-  dd <-
-    dd |> dplyr::mutate(
-      select_choices_or_calculations = dplyr::if_else(
-        is.na(factor_levels),
-        select_choices_or_calculations,
-        factor_levels
-      )
-    )
-
-  list(
-    data = data |>
-      time_only_correction(sel.pos = time.var.sel.pos, sel.neg = time.var.sel.neg) |>
-      hms2character() |>
-      (\(x)stats::setNames(x, tolower(names(x))))(),
-    meta = dd
-  )
-}
-
-### Completion
-#' Completion marking based on completed upload
-#'
-#' @param upload output list from `REDCapR::redcap_write()`
-#' @param ls output list from `ds2dd_detailed()`
-#'
-#' @return list with `REDCapR::redcap_write()` results
-mark_complete <- function(upload, ls){
-  data <- ls$data
-  meta <- ls$meta
-  forms <- unique(meta$form_name)
-  cbind(data[[1]][data[[1]] %in% upload$affected_ids],
-        data.frame(matrix(2,ncol=length(forms),nrow=upload$records_affected_count))) |>
-    stats::setNames(c(names(data)[1],paste0(forms,"_complete")))
-}

R/redcapcast_data.R

@@ -10,9 +10,8 @@
 #'   \item{redcap_repeat_instrument}{Repeat instrument, character}
 #'   \item{redcap_repeat_instance}{Repeat instance, numeric}
 #'   \item{cpr}{CPR number, character}
-#'   \item{inclusion}{Inclusion date, Date}
+#'   \item{inclusion}{Inclusion date, date}
-#'   \item{inclusion_time}{Inclusion time, hms}
+#'   \item{dob}{Date of birth, date}
-#'   \item{dob}{Date of birth, Date}
 #'   \item{age}{Age decimal, numeric}
 #'   \item{age_integer}{Age integer, numeric}
 #'   \item{sex}{Legal sex, character}
@@ -22,10 +21,10 @@
 #'   \item{region}{region, character}
 #'   \item{baseline_data_start_complete}{Completed, character}
 #'   \item{mrs_assessed}{mRS Assessed, character}
-#'   \item{mrs_date}{Assesment date, Date}
+#'   \item{mrs_date}{Assesment date, date}
-#'   \item{mrs_score}{Categorical score, numeric}
+#'   \item{mrs_score}{Score, numeric}
 #'   \item{mrs_complete}{Complete, numeric}
-#'   \item{event_datetime}{Event datetime, POSIXct}
+#'   \item{event_date}{Event date, date}
 #'   \item{event_type}{Event type, character}
 #'   \item{new_event_complete}{Completed, character}
 #'

man/ds2dd.Rd

@@ -2,7 +2,7 @@
 % Please edit documentation in R/ds2dd.R
 \name{ds2dd}
 \alias{ds2dd}
-\title{(DEPRECATED) Data set to data dictionary function}
+\title{Data set to data dictionary function}
 \usage{
 ds2dd(
   ds,
@@ -11,7 +11,7 @@ ds2dd(
   field.type = "text",
   field.label = NULL,
   include.column.names = FALSE,
-  metadata = metadata_names
+  metadata = names(redcapcast_meta)
 )
 }
 \arguments{
@@ -34,18 +34,14 @@ names.}
 column names for original data set for upload.}
 
 \item{metadata}{Metadata column names. Default is the included
-REDCapCAST::metadata_names.}
+REDCapCAST::redcapcast_data.}
 }
 \value{
 data.frame or list of data.frame and vector
 }
 \description{
-Creates a very basic data dictionary skeleton. Please see `ds2dd_detailed()`
-for a more advanced function.
-}
-\details{
 Migrated from stRoke ds2dd(). Fits better with the functionality of
-'REDCapCAST'.
+'REDCapCAST'
 }
 \examples{
 redcapcast_data$record_id <- seq_len(nrow(redcapcast_data))

man/ds2dd_detailed.Rd

@@ -1,82 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ds2dd_detailed.R
-\name{ds2dd_detailed}
-\alias{ds2dd_detailed}
-\title{Extract data from stata file for data dictionary}
-\usage{
-ds2dd_detailed(
-  data,
-  add.auto.id = FALSE,
-  date.format = "dmy",
-  form.name = NULL,
-  field.type = NULL,
-  field.label = NULL,
-  field.label.attr = "label",
-  field.validation = NULL,
-  metadata = metadata_names,
-  validate.time = FALSE,
-  time.var.sel.pos = "[Tt]i[d(me)]",
-  time.var.sel.neg = "[Dd]at[eo]"
-)
-}
-\arguments{
-\item{data}{data frame}
-
-\item{add.auto.id}{flag to add id column}
-
-\item{date.format}{date format, character string. ymd/dmy/mdy. dafault is
-dmy.}
-
-\item{form.name}{manually specify form name(s). Vector of length 1 or
-ncol(data). Default is NULL and "data" is used.}
-
-\item{field.type}{manually specify field type(s). Vector of length 1 or
-ncol(data). Default is NULL and "text" is used for everything but factors,
-which wil get "radio".}
-
-\item{field.label}{manually specify field label(s). Vector of length 1 or
-ncol(data). Default is NULL and colnames(data) is used or attribute
-`field.label.attr` for haven_labelled data set (imported .dta file with
-`haven::read_dta()`).}
-
-\item{field.label.attr}{attribute name for named labels for haven_labelled
-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 file with
-`haven::read_dta()`).}
-
-\item{metadata}{redcap metadata headings. Default is
-REDCapCAST:::metadata_names.}
-
-\item{validate.time}{Flag to validate guessed time columns}
-
-\item{time.var.sel.pos}{Positive selection regex string passed to
-`gues_time_only_filter()` as sel.pos.}
-
-\item{time.var.sel.neg}{Negative selection regex string passed to
-`gues_time_only_filter()` as sel.neg.}
-}
-\value{
-list of length 2
-}
-\description{
-Extract data from stata file for data dictionary
-}
-\details{
-This function is a natural development of the ds2dd() function. It assumes
-that the first column is the ID-column. No checks.
-Please, do always inspect the data dictionary before upload.
-
-Ensure, that the data set is formatted with as much information as possible.
-
-`field.type` can be supplied
-}
-\examples{
-data <- redcapcast_data
-data |> ds2dd_detailed(validate.time = TRUE)
-data |> ds2dd_detailed()
-iris |> ds2dd_detailed(add.auto.id = TRUE)
-mtcars |> ds2dd_detailed(add.auto.id = TRUE)
-}

man/guess_time_only_filter.Rd

@@ -1,36 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ds2dd_detailed.R
-\name{guess_time_only_filter}
-\alias{guess_time_only_filter}
-\title{Try at determining which are true time only variables}
-\usage{
-guess_time_only_filter(
-  data,
-  validate = FALSE,
-  sel.pos = "[Tt]i[d(me)]",
-  sel.neg = "[Dd]at[eo]"
-)
-}
-\arguments{
-\item{data}{data set}
-
-\item{validate}{flag to output validation data. Will output list.}
-
-\item{sel.pos}{Positive selection regex string}
-
-\item{sel.neg}{Negative selection regex string}
-}
-\value{
-character vector or list depending on `validate` flag.
-}
-\description{
-This is just a try at guessing data type based on data class and column names
-hoping for a tiny bit of naming consistency. R does not include a time-only
-data format natively, so the "hms" class from `readr` is used. This
-has to be converted to character class before REDCap upload.
-}
-\examples{
-data <- redcapcast_data
-data |> guess_time_only_filter()
-data |> guess_time_only_filter(validate = TRUE) |> lapply(head)
-}

man/hms2character.Rd

@@ -1,21 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ds2dd_detailed.R
-\name{hms2character}
-\alias{hms2character}
-\title{Change "hms" to "character" for REDCap upload.}
-\usage{
-hms2character(data)
-}
-\arguments{
-\item{data}{data set}
-}
-\value{
-data.frame or tibble
-}
-\description{
-Change "hms" to "character" for REDCap upload.
-}
-\examples{
-data <- redcapcast_data
-## data |> time_only_correction() |> hms2character()
-}

man/mark_complete.Rd

@@ -1,19 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ds2dd_detailed.R
-\name{mark_complete}
-\alias{mark_complete}
-\title{Completion marking based on completed upload}
-\usage{
-mark_complete(upload, ls)
-}
-\arguments{
-\item{upload}{output list from `REDCapR::redcap_write()`}
-
-\item{ls}{output list from `ds2dd_detailed()`}
-}
-\value{
-list with `REDCapR::redcap_write()` results
-}
-\description{
-Completion marking based on completed upload
-}

man/redcapcast_data.Rd

@@ -12,9 +12,8 @@ A data frame with 22 variables:
   \item{redcap_repeat_instrument}{Repeat instrument, character}
   \item{redcap_repeat_instance}{Repeat instance, numeric}
   \item{cpr}{CPR number, character}
-  \item{inclusion}{Inclusion date, Date}
+  \item{inclusion}{Inclusion date, date}
-  \item{inclusion_time}{Inclusion time, hms}
+  \item{dob}{Date of birth, date}
-  \item{dob}{Date of birth, Date}
   \item{age}{Age decimal, numeric}
   \item{age_integer}{Age integer, numeric}
   \item{sex}{Legal sex, character}
@@ -24,10 +23,10 @@ A data frame with 22 variables:
   \item{region}{region, character}
   \item{baseline_data_start_complete}{Completed, character}
   \item{mrs_assessed}{mRS Assessed, character}
-  \item{mrs_date}{Assesment date, Date}
+  \item{mrs_date}{Assesment date, date}
-  \item{mrs_score}{Categorical score, numeric}
+  \item{mrs_score}{Score, numeric}
   \item{mrs_complete}{Complete, numeric}
-  \item{event_datetime}{Event datetime, POSIXct}
+  \item{event_date}{Event date, date}
   \item{event_type}{Event type, character}
   \item{new_event_complete}{Completed, character}
 

man/time_only_correction.Rd

@@ -1,25 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ds2dd_detailed.R
-\name{time_only_correction}
-\alias{time_only_correction}
-\title{Correction based on time_only_filter function. Introduces new class for easier
-validation labelling.}
-\usage{
-time_only_correction(data, ...)
-}
-\arguments{
-\item{data}{data set}
-
-\item{...}{arguments passed on to `guess_time_only_filter()`}
-}
-\value{
-tibble
-}
-\description{
-Dependens on the data class "hms" introduced with
-`guess_time_only_filter()` and converts these
-}
-\examples{
-data <- redcapcast_data
-## data |> time_only_correction()
-}