Statistical Analysis with Missing Data, Third Edition

By Roderick J. A. Little, Donald B. Rubin. Wiley Series in Probability and Statistics, 2019

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Regression imputation in the functional linear model with missing values in the response (2019, background): “of missing data (see [20, 15] for a wide introduction in the multivariate framework).”
Preferred reporting items for systematic reviews and meta‐analyses in ecology and evolutionary biology: a PRISMA extension (2021, methodology): “…analysis as a method of dealing with missing data, but it is important to be explicit about this step, both for the sample size implications (Item 20) and because of the potential to introduce bias when data are not ‘missing completely at random’ (Nakagawa & Freckleton, 2008; Little & Rubin, 2020).”