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This wiki contains notes on using the detect_fu_interviews_public repository. This GitHub repository (i.e., brad-cannell/detect_fu_interviews_public) contains the statistical programming code that was used to clean the DETECT Follow-Up Interviews data and prepare it for analysis (most of it written in the R language).
Here's a quick overview of how to start working with the DETECT Follow-Up Interviews data. Additional details are provided on the topic-specific pages available in the table of contents on the right-hand side of the screen.
To get started, you will want to make sure you have R and RStudio installed on your computer. If you don't know how to install them, you can find instructions in R for Epidemiology or on RStudio's website. Additionally, the majority of the code files are saved in the Quarto file format. If you are unfamiliar with Quarto files, you can read more about them in R for Epidemiology or on the Quarto homepage.
This section gives instructions for analyzing the cleaned DETECT Follow-Up Interviews data, as opposed to modifying the cleaned DETECT Follow-Up Interviews data.
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View or download the codebook. Please view the Codebooks wiki page for more information.
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Download the data. Please view the DETECT Data wiki page for more information.
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Complete your data analysis.
This section gives instructions for modifying the cleaned DETECT Follow-Up Interviews data. Again, this should not be done frequently, and should never be done without notifying the project's principal investigator.
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Clone the repository. Please view the Cloning the Repository wiki page for more information.
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Download the data. Please view the DETECT Data wiki page for more information.
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Begin editing the code files. Please view the File Structure wiki page for more information about the purpose of each file.
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Create a pull request to request that the changes you made to the code files be permanently incorporated into the repository. If you are unfamiliar with pull requests, you can learn more about them in R for Epidemiology or in the GitHub documentation.
To make the data as transparent and easy to maintain as possible, this public wiki includes other pages that discuss why various other data management decisions were made and how they were implemented. Please use the navigation pane on the right side of this screen to view them.