Which concept states that missingness itself is related to the outcome?

Which concept states that missingness itself is related to the outcome?

• A. Exploratory Data Analysis (EDA)
• B. Categorical Data
• C. Longitudinal data
• D. Informative Missingness

Answer: (D)

Informative missingness, also known as missing not at random, is the idea that whether a value is missing depends on the value of the missing data or the outcome itself. Because the missingness carries information about the outcome, standard analyses that assume data are missing at random or missing completely at random can be biased if this mechanism isn't accounted for. For example, patients with more severe symptoms might be more likely to drop out, so the fact that their follow-up data are missing is related to the outcome you want to study. This requires methods that explicitly model the missingness mechanism or perform sensitivity analyses to assess how results change under different MNAR assumptions. The other options describe data types or analysis approaches, not the concept that missingness is tied to the outcome itself.

Informative missingness, also known as missing not at random, is the idea that whether a value is missing depends on the value of the missing data or the outcome itself. Because the missingness carries information about the outcome, standard analyses that assume data are missing at random or missing completely at random can be biased if this mechanism isn't accounted for. For example, patients with more severe symptoms might be more likely to drop out, so the fact that their follow-up data are missing is related to the outcome you want to study. This requires methods that explicitly model the missingness mechanism or perform sensitivity analyses to assess how results change under different MNAR assumptions. The other options describe data types or analysis approaches, not the concept that missingness is tied to the outcome itself.