andreas/REDCapCAST
1
0
Fork 0
mirror of https://github.com/agdamsbo/REDCapCAST.git synced 2024-11-22 05:20:23 +01:00
Code Issues Packages Projects Releases Wiki Activity

Improved instructions for R package in README.md.

Browse Source
This commit is contained in:
Egeler, Paul W 2018-06-03 17:09:26 -04:00
parent 2cf5c8e019
commit a1297903c2
1 changed files with 49 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

53
README.md
View File

@ -35,6 +35,8 @@ a solution to handle the problem in both SAS and R.
## Instructions
### R
#### Installation
First you must install the package. To do so, execute the following in your R console:
```r
@ -42,14 +44,57 @@ if (!require(devtools)) install.packages("devtools")
devtools::install_github("SpectrumHealthResearch/REDCapRITS/R")
```
#### Usage
After the package is installed, follow these instructions:
1. Download the record dataset and metadata. This can
be accomplished either by traditional methods or using the API. The
`read.csv()` function should be able to handle newline characters within
records, so no pre-processing of metadata csv is needed.
be accomplished either by traditional methods or using the API.
1. Call the function, pointing it to your record dataset and metadata
`data.frame`s or JSON character vectors.
`data.frame`s or JSON character vectors. You may need to load the package via
`library()` or `require()`.
#### Examples
Here is an example usage in conjuction with an API call to your REDCap instance:
```r
library(RCurl)
# Get the records
records <- postForm(
uri = api_url, # Supply your site-specific URI
token = api_token, # Supply your own API token
content = 'record',
format = 'json',
returnFormat = 'json'
)
# Get the metadata
metadata <- postForm(
uri = api_url,
token = api_token,
content = 'metadata',
format = 'json'
)
# Convert exported JSON strings into a list of data.frames
REDCapRITS::REDCap_split(records, metadata)
```
And here is an example of usage when downloading a REDCap export manually from your REDCap web interface:
```r
# Get the records
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")
# Split the tables
REDCapRITS::REDCap_split(records, metadata)
```
### SAS