Part 2: Missing At Random (MAR) in Stata

Understanding Missing Data Mechanisms in Applied Research: Part 2 – Missing At Random (MAR) in Stata

In applied research, missing data are rarely completely random. Most real-world datasets exhibit systematic patterns of missingness that depend on observable characteristics. Understanding these patterns is essential because they determine whether standard analytical methods remain valid and whether results can be defended in peer-reviewed work.