The missing peak: a worked missing-not-at-random example

An apparently complete environmental record can underestimate its target when high values are less likely to be retained. This methods note presents a wholly fictional 100-value index series whose response-dependent missingness lowers the observed mean. It compares zero replacement, complete-case averaging, mean imputation, interpolation, and model-based assumptions, then expresses the complete-period mean as a function of the unknown missing-value mean. A sensitivity table and an educational tipping point make the unidentifiable component explicit. Seaman and colleagues' missingness definitions, CF conventions, and observing-network context frame the analysis. No empirical correction, safety threshold, or acceptable completeness percentage is proposed. The note argues for preserving failure information and reporting assumption-dependent conclusions rather than allowing a smooth completed series to conceal selection.