Sensitivity analysis after multiple imputation under missing at random: a weighting approach

DOI10.1177/0962280206075303zbMath1122.62300OpenAlexW2085438886WikidataQ36875584 ScholiaQ36875584MaRDI QIDQ5425042

James Carpenter, Michael G. Kenward, Ian R. White

Publication date: 7 November 2007

Published in: Statistical Methods in Medical Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/0962280206075303

Mathematics Subject Classification ID

Related Items (12)

Posterior predictive checking of multiple imputation models ⋮ Multiple imputation for nonignorable missing data ⋮ A shared parameter mixture model for longitudinal income data with missing responses and zero rounding ⋮ Treatment of nonignorable missing data when modeling unobserved heterogeneity with finite mixture models ⋮ Addressing missing data mechanism uncertainty using multiple-model multiple imputation: application to a longitudinal clinical trial ⋮ Unnamed Item ⋮ Variable selection techniques after multiple imputation in high-dimensional data ⋮ Unnamed Item ⋮ Comments on: Missing data methods in longitudinal studies: a review ⋮ Variable selection models based on multiple imputation with an application for predicting median effective dose and maximum effect ⋮ A cautionary case study of approaches to the treatment of missing data ⋮ Assessing the Sensitivity of Meta-analysis to Selection Bias: A Multiple Imputation Approach

Cites Work

• Sensitivity analysis for informative censoring in parametric survival models
• Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes

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