Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
March 23, 2024MathematicsOpen Access

Imputation-Based Variable Selection Method for Block-Wise Missing Data When Integrating Multiple Longitudinal Studies

View Full Paper
Ask AI
Bookmark
Share

Authors

ZOZhongzhe OuyangLWLu Wang

Discussion

Loading...

Member takes

Overview

Key Points

Key points are not available for this paper at this time.

Cite This Study

Ouyang et al. (2024) studied this question.

synapsesocial.com/papers/68e72b90b6db6435876a4efchttps://doi.org/10.3390/math12070951
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Simultaneous variable selection and parameters estimation for longitudinal data subject to missingness and covariates measurement error2024
  2. 2Flexible variable selection in the presence of missing data2024 · 1 citations
  3. 3How to apply Bayesian stochastic search variable selection with multiply imputed data.2026
  4. 4Evaluating Bayesian Variable Selection Approaches for Nonlinear Random Effects Models2026
  5. 5Bayesian variable selection for joint models of heterogeneous longitudinal variables and a binary outcome2026