mirror of
https://github.com/agdamsbo/stRoke.git
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88 lines
2.3 KiB
Plaintext
88 lines
2.3 KiB
Plaintext
---
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title: "ds2dd"
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date: "`r Sys.Date()`"
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output: rmarkdown::html_vignette
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vignette: >
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%\VignetteIndexEntry{ds2dd}
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%\VignetteEngine{knitr::rmarkdown}
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%\VignetteEncoding{UTF-8}
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---
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```{r, include = FALSE}
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knitr::opts_chunk$set(
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collapse = TRUE,
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comment = "#>"
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)
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```
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```{r setup}
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library(stRoke)
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```
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# Easy data set to data base workflow
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This function can be used as a simple tool for creating at data base metadata file for REDCap (called a DataDictionary) based on a given data set file.
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## Step 1 - Load your data set
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Here we'll use the sample TALOS dataset included with the package.
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```{r}
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data("talos")
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ds <- talos
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# As the data set lacks an ID column, one is added
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ds$id <- seq_len(nrow(ds))
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```
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## Step 2 - Create the DataDictionary
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```{r}
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datadictionary <- ds2dd(ds,record.id = "id",include.column.names = TRUE)
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```
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Now 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.
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The function will transform column names to lower case and substitute spaces for underscores. The output is a list with the DataDictionary and a vector of new column names for the dataset to fit the meta data.
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## Step 3 - Meta data upload
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Now the DataDictionary can be exported as a spreadsheet and uploaded or it can be uploaded using the `REDCapR` package (only projects with "Development" status).
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Use one of the two approaches below:
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### Manual upload
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```{r eval=FALSE}
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write.csv(datadictionary$DataDictionary,"datadictionary.csv")
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```
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### Upload with `REDCapR`
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```{r eval=FALSE}
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REDCapR::redcap_metadata_write(
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datadictionary$DataDictionary,
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redcap_uri = keyring::key_get("DB_URI"),
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token = keyring::key_get("DB_TOKEN")
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)
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```
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In the ["REDCap R Handbook"](https://agdamsbo.github.io/redcap-r-handbook/) more is written on interfacing with REDCap in R using the `library(keyring)`to store credentials in [chapter 1.1](https://agdamsbo.github.io/redcap-r-handbook/access.html#sec-getting-access).
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## Step 4 - Data upload
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The same two options are available for data upload as meta data upload: manual or through `REDCapR`.
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Only the latter is shown here.
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```{r eval=FALSE}
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# new column names are applied
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colnames(ds) <- datadictionary$`Column names`
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REDCapR::redcap_write(
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ds,
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redcap_uri = keyring::key_get("DB_URI"),
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token = keyring::key_get("DB_TOKEN")
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)
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```
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