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cleaning up illustration in README.md
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README.md
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README.md
@ -24,13 +24,15 @@ way that is not useful in most analysis software.
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The normalized data can be retrieved by downloading repeating instruments individually then doing a little
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data munging or by writing a few custom parameters in a series of API calls (then doing more data munging),
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but this is a lot of extra steps that can make reproducible research more difficult.
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Therefore, I have made a programmatic solution to handle the problem in both SAS and R.
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REDCapRITS is a programmatic solution to handle the problem in both SAS and R.
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### Illustration
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For example, consider this mocked-up data involving some information about a subset
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of cars in R's built-in `mtcars` dataset (1). Contained in the data is a repeating instrument,
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*sales*, which contains sales transaction data for some of those cars.
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For example, consider this mocked-up data exported from a REDCap project with repeating instruments.
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The data contains information on a subset of cars in R's built-in `mtcars` dataset [1].
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Within the table there is also a repeating instrument, *sales*, which has sales transaction
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data for some of those cars.
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| car_id|redcap_repeat_instrument |redcap_repeat_instance |make |model |mpg |cyl |motor_trend_cars_complete |price |color |customer |sale_complete |
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|------:|:------------------------|:----------------------|:--------|:-----------|:----|:---|:-------------------------|:--------|:-----|:--------|:-------------|
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@ -59,7 +61,7 @@ of cars in R's built-in `mtcars` dataset (1). Contained in the data is a repeati
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| 10|sale |3 | | | | | |6800.55 |3 |Sharon |2 |
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You can see that the data from the non-repeating forms (primary table) is interlaced with the data in the repeating forms,
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You can see that the data from the non-repeating form (primary table) is interlaced with the data in the repeating form,
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creating a checkerboard pattern. In order to do analysis, the data must be normalized and then the tables rejoined.
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Normalization would result in two tables: 1) a *primary* table and 2) a *sale* table.
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The normalized tables would look like this:
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@ -98,7 +100,7 @@ The normalized tables would look like this:
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|10 |sale |3 |6800.55 |3 |Sharon |2 |
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Suppose you would like to do some analysis such as sale price by make of car or find
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the most popular color for each model. To do so, you can join the tables together using
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the most popular color for each model. To do so, you can join the tables together with
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relational algebra. After inner joining the *primary* table to the *sale* table on `car_id`
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and selecting only the fields you are interested in,
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your resulting analytic dataset might look something like this:
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@ -126,7 +128,7 @@ Such a join can be accomplished numerous ways. Just to name a few:
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- The [`MERGE`](http://support.sas.com/documentation/cdl/en/lrdict/64316/HTML/default/viewer.htm#a000202970.htm) statement in a `DATA` step
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- R
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- [`dplyr::*_join`](https://www.rdocumentation.org/packages/dplyr/versions/0.7.5/topics/join)
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- [`sqldf`](https://www.rdocumentation.org/packages/sqldf/versions/0.4-11/topics/sqldf)
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- [`sqldf::sqldf`](https://www.rdocumentation.org/packages/sqldf/versions/0.4-11/topics/sqldf)
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- [`base::merge`](https://www.rdocumentation.org/packages/base/versions/3.5.0/topics/merge)
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### Supported Platforms
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@ -273,11 +275,11 @@ Suggestions and contributions are more than welcome! Please feel free to create
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## About REDCap
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This code was written for [REDCap electronic data capture tools](https://projectredcap.org/)(2). Code for this project was tested on the REDCap instance hosted at Spectrum Health, Grand Rapids, MI. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing 1) an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources.
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This code was written for [REDCap electronic data capture tools](https://projectredcap.org/) [2]. Code for this project was tested on the REDCap instance hosted at Spectrum Health, Grand Rapids, MI. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing 1) an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources.
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## References
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(1) Henderson and Velleman (1981), Building multiple regression models interactively. *Biometrics*, **37**, 391--411.
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[1] Henderson and Velleman (1981), Building multiple regression models interactively. *Biometrics*, **37**, 391--411.
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**Modified with fake data for the purpose of illustration**
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(2) Paul A. Harris, Robert Taylor, Robert Thielke, Jonathon Payne, Nathaniel Gonzalez, Jose G. Conde, Research electronic data capture (REDCap) – A metadata-driven methodology and workflow process for providing translational research informatics support, J Biomed Inform. 2009 Apr;42(2):377-81.
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[2] Paul A. Harris, Robert Taylor, Robert Thielke, Jonathon Payne, Nathaniel Gonzalez, Jose G. Conde, Research electronic data capture (REDCap) – A metadata-driven methodology and workflow process for providing translational research informatics support, J Biomed Inform. 2009 Apr;42(2):377-81.
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