CLiREN-LMS
Data Cleaning and Preparation in R

The Purpose of Data Cleaning and Preparation

Knowledge Check

30-45 minutes Applied Step 21 of 23
Quiz

Knowledge Check

21 / 23
Quiz

Knowledge Check

What is the best description of raw data in an R cleaning workflow?
  • A. Data received from the source system without manual alteration
  • B. Data after all derived variables have been created
  • C. Data with all missing values removed
  • D. Data copied into a report table
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Answer: A

Why should R not become a hidden place for silently altering clinical data?
  • A. Silent changes undermine traceability and may bypass the source database audit trail
  • B. R cannot write files
  • C. REDCap exports never contain errors
  • D. Data cleaning is only a statistical task
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Answer: A

Which activity is best described as data preparation rather than correction?
  • A. Deriving age at enrollment from date of birth and consent date
  • B. Correcting a wrong admission date after source document review
  • C. Changing a primary outcome after investigator adjudication
  • D. Deleting a duplicated record without documentation
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Answer: A

What should usually happen when R identifies an impossible date sequence in a clinical database?
  • A. Generate a query for review and correct the source database through the approved workflow
  • B. Replace the dates in the raw CSV file
  • C. Ignore the record
  • D. Delete the participant from all outputs
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Answer: A