Year: 2025
Type: article
Abstract: As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness (SM), encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom missingness. We highlight the challenges that this brings, especially in relation to imputation. We point out that the effectiveness of imputation depends on missingness structure, showing how the missingness structure interacts with the nature of the data. Lastly, we give guidance on handling SM in integrated data, especially in relation to imputation.
Source: Advanced Intelligent Discovery
Authors: James Jackson, Marius Hofert, Eleni‐Rosalina Andrinopoulou, Niels Hagenbuch, Sarah McGough, Chris Harbron, Robin Mitra
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4415029639