When Is a Complete-Case Approach to Missing Data Valid? The Importance of Effect-Measure Modification
By anna [dot] axmon [at] med [dot] lu [dot] se (Anna Axmon) - published 29 May 2021 When estimating causal effects, careful handling of missing data is needed to avoid bias. Complete-case analysis is commonly used in epidemiologic analyses. Previous work has shown that covariate-stratified effect estimates from complete-case analysis are unbiased when missingness is independent of the outcome cond
https://www.lupop.lu.se/article/when-complete-case-approach-missing-data-valid-importance-effect-measure-modification - 2025-04-01