Dissecting multiple imputation from a multi-phase inference perspective: what happens when God’s, imputer’s and analyst’s models are uncongenial?

DOI10.5705/ss.2014.067zbMath1392.62040OpenAlexW2900898685MaRDI QIDQ4601241

Xianchao Xie, Xiao-Li Meng

Publication date: 12 January 2018

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5705/ss.2014.067

zbMATH Keywords

incomplete datadata cleaningpre-processingstrong efficiencyconfidence validityuncongenialityestimating equation decompositionmulti-phase inferenceself-efficiency

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05) Foundations and philosophical topics in statistics (62A01)

Related Items

General and feasible tests with multiply-imputed datasets, Leveraging random assignment to impute missing covariates in causal studies, Multiple Improvements of Multiple Imputation Likelihood Ratio Tests, Recent Developments in Dealing with Item Non‐response in Surveys: A Critical Review, Multiple imputation: a review of practical and theoretical findings