Part 1: Missing Completely at Random (MCAR) in Stata

Understanding Missing Data Mechanisms in Applied Research: Part 1 – Missing Completely at Random (MCAR)

Missing data is not primarily a software issue, it is a research design and data-generating process problem. The way missingness occurs determines whether statistical estimates are unbiased, whether standard errors are valid, and ultimately whether research findings are credible and publishable. Treating missing data as a purely technical inconvenience often leads to incorrect conclusions, even when advanced software tools are used correctly.