MNARi

MNARi is a term used in statistics and data analysis to describe a specific type of missing data mechanism. It stands for Missing Not At Random, but more specifically, it implies that the probability of a value being missing depends on the unobserved missing value itself, and potentially on observed values as well. This is a more complex scenario than Missing Completely At Random (MCAR) or Missing At Random (MAR).

In MNAR data, the reason for a value being missing is directly related to the value that is missing. For example, individuals with very high incomes might be less likely to report their income in a survey. In this case, the missingness of the income value is dependent on the income value itself. This makes it challenging to handle missing data because simply ignoring or imputing values based on observed data can lead to biased results.

Statistical techniques designed to handle MNAR data often require making specific assumptions about the missing data mechanism, which can be difficult to verify. These methods might involve modeling the missingness process itself or using more sophisticated imputation strategies. Researchers must carefully consider the potential for MNAR data when designing studies and analyzing results, as it can significantly impact the validity of conclusions. Distinguishing between MAR and MNAR can be particularly difficult, and often requires domain knowledge or sensitivity analyses.