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README.md

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+REDCap Repeating Instrument Table Splitter
+===========================================
+
+Paul W. Egeler, M.S., GStat
+Spectrum Health Office of Research Administration
+13 July 2017
+
+## Description
+
+So the new buzz in the REDCap world seems to be Repeating Instruments 
+and Events. Certainly there is potential for a lot of utility in this 
+feature and I was excited to try it out. I know I will be using this 
+feature a lot in the future.
+
+Unfortunately, I was not very happy with the way the data was exported 
+either via CSV or API call. When you conceptualize the data model for 
+a Repeating Instrument, you probably think of a multi-table model. You 
+might expect that the non-repeating instruments may constitute one table 
+that would be related to Repeating Instruments tables via a one-to-many 
+relationship. In reality, the data is outputted as one table with all 
+possible fields; this has the effect of nesting the output table in a 
+way that is not useful in most analysis software. Therefore, I have made 
+a solution to handle the problem in both SAS and R.
+
+## Instructions
+
+### SAS
+
+1. Run the macro definition in the source editor or using `%include`.
+2. Run the SAS code provided by REDCap to import the data BUT COMMENT 
+THIS LINE:
+    `format redcap_repeat_instrument redcap_repeat_instrument_.;`
+3. Open the data dictionary in MS Excel. We will need to do some pre-
+processing to the data dictionary file before reading it in because
+some of the user entry points (such as **Field Label**) allows for newline
+characters, which can break our data ingestion. MS Excel will read in
+the newline characters correctly.
+    - Copy the first four columns and paste into a new sheet.
+    - Save the new sheet as a .csv file.
+    - Close the file.
+4. Call the macro, adjusting parameters as needed.
+
+### R
+
+The function definition file contains an example to assist you.
+
+1. Run the function definition in the source editor or using `source()`.
+2. Download the record dataset and metadata and import them. 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.
+3. Call the function, pointing it to your record dataset and metadata
+`data.frame`s.