New variants of multiple imputation, NAR-SMCFCS and NAR-SMC-stack, keep imputation compatible with a causal analysis model when the outcome causes its own missingness, and reduce bias in estimated effects.
Multiple-imputation inferences with uncongenial sources of input
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Sensitivity analysis methods for outcome missingness using substantive-model-compatible multiple imputation and their application in causal inference
New variants of multiple imputation, NAR-SMCFCS and NAR-SMC-stack, keep imputation compatible with a causal analysis model when the outcome causes its own missingness, and reduce bias in estimated effects.