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Server Data Organization Instructions.md

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Server Data - Data Organization Instructions

NOTE: The month for the timestamp ranges from 0-11 . Thus, January is actually indicated by a 0, February is actually indicated by 1, and so forth. Please remember to keep this in mind.

Get, Splice, and Clean Data

Download our Get, Splice, and Clean Data.R script. We include detailed comments throughout our R Script describing what each line is doing. Below we point out the lines that require modifications.

Get Necessary Libraries

  1. Lines 2 to 6 load the libraries you'll need to get, splice, and clean your ExperienceSampler Server Data.
  • If you do not have the tidyr, stringr, and plyr libraries, uncomment line 3 to install the packages.

Get, Splice, and Clean Server Data

  1. Create a folder to store your raw data on your computer.
  2. Copy this directory and paste it between the double quotation marks in lines 9, 29, and 41.
  3. In line 13, insert the server URL where the URL placeholder is.
  • This is what precedes data_collector.cgi in your saveData and saveLastPageData functions.
  1. In line 23, set the range of participant IDs. Presumably this is a range of numbers that has been assigned sequentially.
  2. If there are missing participant IDs, you will need to make a vector of missing ids in line 25.
  • If there is are no missing participant IDs, comment out lines 25 and 27.
  1. In lines 81-91, enter all the unique key values that are not associated with real data such as pause, notification, snoozed, etc.
  2. Create a new folder to save your spliced data on your computer.
  3. Copy this directory and paste it between the double quotation marks in lines 100 and 109.
  • Do NOT store in your spliced data in the same folder as your raw data.
  1. In line 119, set the directory to be different from spliced data folder.
  2. Highlight and run the entire script.

Convert to Long Form

Download our Convert Data.R script. We include detailed comments throughout our R Script describing what each line is doing and some instructions. Below we point out the lines that require modifications.

This process is the same for both Server and Google Data.

Get Necessary Libraries

  1. Lines 2 to 6 load the libraries you'll need to get, splice, and clean your ExperienceSampler Server Data.
  • If you do not have the tidyr, stringr, and plyr libraries, uncomment line 3 to install the packages.

Convert Data

  1. In line 9, set the directory to where the merged spliced data file is.
  2. Starting from line 28, you can correct any weird variable names.
  • Sometimes ExperienceSampler will append a "1" or a "-" to variable names. You want to ensure that values for the same variable are written in the same column, so you need to correct this.
  • We included examples in lines 28 to 30. There are three arguments for this function:
    • First Argument: The original variable name (aka the weird variable name)
    • Second Argument: The corrected variable name (aka what you want to replace the weird variable name with)
    • Third Argument: The column
  1. If you missed any variable names that are not associated with usable data, you can delete them in line 34.
  • Just input the row numbers.
  1. Starting from line 49, copy and paste the lines starting from 28
  • This renames the variables in the ACTUAL spliced dataset
  1. If you wish to reorganize the columns in your dataset, uncomment lines 92 - 103.
  • Rearrange them by typing the variable names in the order you desire. Each variable name should appear between the quotation marks.
  1. In line 114, set the directory for where you want your long form data to be saved. You can rename the long form data file in line 115 if you want.
  2. Run each line by itself in the PREPARATION section. Inspect the variable names carefully.
  3. Highlight and run all the lines from the CONVERSION section to the end of the script.