Calibration and Multiple Robustness When Data Are Missing Not At Random

DOI10.5705/SS.202015.0408zbMath1406.62048OpenAlexW2895004019MaRDI QIDQ4558440

Peisong Han

Publication date: 22 November 2018

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

Full work available at URL: https://doi.org/10.5705/ss.202015.0408

zbMATH Keywords

calibrationempirical likelihoodmultiple robustnessnonignorable nonresponsemissing not at random (MNAR)

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Sampling theory, sample surveys (62D05)

Related Items (5)

Quantile Regression for Nonignorable Missing Data with Its Application of Analyzing Electronic Medical Records ⋮ Calibration Techniques Encompassing Survey Sampling, Missing Data Analysis and Causal Inference ⋮ A semiparametric multiply robust multiple imputation method for causal inference ⋮ Calibration estimation of semiparametric copula models with data missing at random ⋮ Penalized multiply robust estimation in high-order autoregressive processes with missing explanatory variables

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