Multiple imputation and other resampling schemes for imputing missing observations

DOI10.1016/j.jmva.2009.06.003zbMath1172.62013OpenAlexW2077461363MaRDI QIDQ842911

Mohammad Dolatabadi, Muni S. Srivastava

Publication date: 28 September 2009

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2009.06.003

zbMATH Keywords

bootstrapresamplingmissing dataregression modelnonresponsejackknife variance estimationcomparison of confidence intervalsmultiple and single imputation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Nonparametric estimation (62G05) Linear inference, regression (62J99) Nonparametric statistical resampling methods (62G09)

Related Items

Multiple imputations and the missing censoring indicator model ⋮ Tests of homoscedasticity, normality, and missing completely at random for incomplete multivariate data ⋮ Empirical likelihood-based inference in nonlinear regression models with missing responses at random

Uses Software

• SenSrivastava

Cites Work

• Unnamed Item
• Asymptotic results for multiple imputation
• Bootstrapping regression models
• Bootstrap methods: another look at the jackknife
• Finite sample properties of multiple imputation estimators.
• Jackknife variance estimation with survey data under hot deck imputation
• Inference and missing data
• Jackknifing in Unbalanced Situations
• Multiple Imputation for Interval Estimation From Simple Random Samples With Ignorable Nonresponse