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November 1, 2025Statistics in MedicineOpen Access

A Bayesian Two‐Step Multiple Imputation Approach Based on Mixed Models for Missing EMA Data

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Authors

YWYiheng WeiJSJuned SiddiqueBSBonnie Spring

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Overview

Simulation study demonstrates the effectiveness of Bayesian multiple imputation for missing data in ecological momentary assessments, highlighting mixed models.

Key Points

  • Bayesian multiple imputation improves handling of missing data in longitudinal studies, enhancing analysis accuracy.
  • Simulation study showed that mixed models effectively addressed missing data issues, increasing robustness.
  • The two-step approach provides a systematic way to evaluate different mixed models for handling missing values.
  • Application to the MBC1 study illustrates significant differences in imputation performance among mixed models.

Cite This Study

Wei et al. (2025) studied this question.

synapsesocial.com/papers/6925437fc0ce034ddc358f5bhttps://doi.org/10.1002/sim.70325
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  4. 4MCMC-Based Bayesian Estimation for Nonlinear Mixed-Effects Models with Missing Data: A Study of Convergence and Computational Efficiency2026
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