An imputation approach for handling mixed-mode surveys

DOI10.1214/16-AOAS930zbMath1398.62382MaRDI QIDQ312973

Seunghwan Park, Sangun Park, Jae Kwang Kim

Publication date: 9 September 2016

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aoas/1469199905

zbMATH Keywords

missing datasurvey samplingcounterfactual outcomefractional imputationmeasurement error model

Mathematics Subject Classification ID

Applications of statistics to social sciences (62P25) Sampling theory, sample surveys (62D05)

Related Items (4)

Statistical data integration in survey sampling: a review ⋮ Estimating mode effects from a sequential mixed-mode experiment using structural moment models ⋮ A measurement error model approach to survey data integration: combining information from two surveys ⋮ Estimation under mode effects and proxy surveys, accounting for non-ignorable nonresponse

Cites Work

• Parametric fractional imputation for missing data analysis
• Monte Carlo methods in Bayesian computation
• Inference and missing data
• Maximizing Generalized Linear Mixed Model Likelihoods With an Automated Monte Carlo EM Algorithm
• Regression Analysis when the Dependent Variable Is Truncated Normal
• Nonparametric Bayesian Multiple Imputation for Missing Data Due to Mid-Study Switching of Measurement Methods
• Likelihood Estimation for Censored Random Vectors
• Measurement Error in Nonlinear Models

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