MCAR vs MAR vs MNAR — what's the difference?

hard

Answer

$MCAR (Missing Completely At Random): missingness independent of both observed and unobserved data.$
$Can drop rows without bias.$
$MAR (Missing At Random): missingness depends only on observed data — imputable given the observed features.$
$MNAR (Missing Not At Random): missingness depends on the unobserved value itself (e.g., high-income people refuse to report income).$
$Only MNAR requires modeling the missingness mechanism.$
$Assumption matters — different methods assume different types.$

Check yourself — multiple choice

All identical
MCAR: fully random; MAR: depends on observed; MNAR: depends on unobserved value — only MNAR needs modeling the mechanism
MNAR = MCAR
MAR is never useful

MCAR / MAR / MNAR: only MNAR requires modeling the missingness.

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