8.2 Missing data mechanisms

• Missing Completely at Random (MCAR)

  • Locations of missing values in the dataset are purely random, they do not depend on any other data.

  • Example: A weather sensor is measuring temperature and sending the data to a database. There are some missing entries in the database for when the sensor broke down.

  • MCAR test (naniar package)

• Missing at Random (MAR)

  • Locations of missing values in the dataset depend on some other, observed data.

  • Example: There are some missing temperature values in the database for when the sensor was switched off for maintenance. As the maintenance team never work on the weekends, the locations of missing values depend on the day of the week.

• Missing Not at Random (MNAR)

  • Locations of missing values in the dataset depend on the missing values themselves.

  • Example: When it’s extremely cold, the weather sensor freezes and stops working. So, it does not record very low temperatures. Thus, the locations of missing values in the temperature variable depend on the values of this variable themselves.