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docs and name update
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@ -58,7 +58,8 @@ Imports:
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zip,
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zip,
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assertthat,
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assertthat,
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openxlsx2,
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openxlsx2,
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readODS
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readODS,
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forcats
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Collate:
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Collate:
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'REDCapCAST-package.R'
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'REDCapCAST-package.R'
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'utils.r'
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'utils.r'
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@ -20,10 +20,14 @@ export(file_extension)
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export(focused_metadata)
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export(focused_metadata)
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export(format_subheader)
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export(format_subheader)
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export(get_api_key)
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export(get_api_key)
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export(guess_time_only)
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export(guess_time_only_filter)
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export(guess_time_only_filter)
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export(haven_all_levels)
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export(html_tag_wrap)
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export(html_tag_wrap)
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export(is_repeated_longitudinal)
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export(is_repeated_longitudinal)
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export(match_fields_to_form)
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export(match_fields_to_form)
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export(numchar2fct)
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export(parse_data)
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export(process_user_input)
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export(process_user_input)
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export(read_input)
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export(read_input)
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export(read_redcap_instrument)
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export(read_redcap_instrument)
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@ -33,9 +37,11 @@ export(sanitize_split)
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export(shiny_cast)
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export(shiny_cast)
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export(split_non_repeating_forms)
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export(split_non_repeating_forms)
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export(strsplitx)
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export(strsplitx)
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export(var2fct)
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importFrom(REDCapR,redcap_event_instruments)
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importFrom(REDCapR,redcap_event_instruments)
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importFrom(REDCapR,redcap_metadata_read)
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importFrom(REDCapR,redcap_metadata_read)
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importFrom(REDCapR,redcap_read)
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importFrom(REDCapR,redcap_read)
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importFrom(forcats,as_factor)
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importFrom(keyring,key_get)
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importFrom(keyring,key_get)
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importFrom(keyring,key_list)
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importFrom(keyring,key_list)
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importFrom(keyring,key_set)
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importFrom(keyring,key_set)
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@ -17,7 +17,8 @@ server <- function(input, output, session) {
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dat <- shiny::reactive({
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dat <- shiny::reactive({
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shiny::req(input$ds)
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shiny::req(input$ds)
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read_input(input$ds$datapath)
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read_input(input$ds$datapath) |>
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parse_data()
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})
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})
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# getData <- reactive({
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# getData <- reactive({
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@ -4,7 +4,7 @@
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\name{REDCapCAST-package}
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\name{REDCapCAST-package}
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\alias{REDCapCAST}
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\alias{REDCapCAST}
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\alias{REDCapCAST-package}
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\alias{REDCapCAST-package}
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\title{REDCapCAST: REDCap Castellated Data Handling And Metadata Casting}
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\title{REDCapCAST: REDCap Castellated Data Handling and Metadata Casting}
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\description{
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\description{
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\if{html}{\figure{logo.png}{options: style='float: right' alt='logo' width='120'}}
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\if{html}{\figure{logo.png}{options: style='float: right' alt='logo' width='120'}}
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@ -45,7 +45,7 @@ The more advanced `ds2dd_detailed()` is a natural development. It will try to ap
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The dataset should be correctly formatted for the data dictionary to preserve as much information as possible.
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The dataset should be correctly formatted for the data dictionary to preserve as much information as possible.
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```{r eval=TRUE}
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```{r eval=FALSE}
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d2 <- REDCapCAST::redcapcast_data |>
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d2 <- REDCapCAST::redcapcast_data |>
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dplyr::mutate(record_id = seq_len(dplyr::n()),
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dplyr::mutate(record_id = seq_len(dplyr::n()),
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region=factor(region)) |>
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region=factor(region)) |>
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@ -2,7 +2,7 @@
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title: "REDCapCAST"
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title: "REDCapCAST"
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output: rmarkdown::html_vignette
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output: rmarkdown::html_vignette
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vignette: >
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vignette: >
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%\VignetteIndexEntry{Introduction}
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%\VignetteIndexEntry{REDCapCAST}
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%\VignetteEngine{knitr::rmarkdown}
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%\VignetteEngine{knitr::rmarkdown}
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%\VignetteEncoding{UTF-8}
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%\VignetteEncoding{UTF-8}
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---
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---
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@ -14,13 +14,34 @@ knitr::opts_chunk$set(
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)
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)
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```
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```
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To make the easiest possible transition from spreadsheet/dataset to REDCap, I have created a small Shiny app, which adds a graphical interface to the casting of a data dictionary and data upload. Install the package and run the app as follows:
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To make the easiest possible transition from spreadsheet/dataset to REDCap, I have created a small app, which adds a graphical interface to the casting of a data dictionary and data upload. Install the package and launch the app as follows:
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```{r eval=FALSE}
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```{r eval=FALSE}
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require(REDCapCAST)
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REDCapCAST::shiny_cast()
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shiny_cast()
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```
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The app primarily wraps one function: `ds2dd_detailed()`.
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```{r}
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REDCap_split(
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records = redcapcast_data,
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metadata = redcapcast_meta,
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forms = "all"
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) |>
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sanitize_split() |>
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redcap_wider() |>
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ds2dd_detailed()|>
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purrr::pluck("data") |>
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readr::type_convert(
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col_types = readr::cols(.default = readr::col_guess()))
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```
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```{r}
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redcapcast_data |>
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dplyr::mutate(dplyr::across(dplyr::everything(),as.character)) |>
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readr::type_convert(
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col_types = readr::cols(.default = readr::col_guess()))
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```
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```
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The app will launch in a new window and the interface should be fairly self-explanatory.
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The app only provides the most basic functionality, but might be extended in the future.
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