Bayesian imputation of time-varying covariates in linear mixed models

Volume: 28, Issue: 2, Pages: 555 - 568
Published: Oct 25, 2017
Abstract
Studies involving large observational datasets commonly face the challenge of dealing with multiple missing values. The most popular approach to overcome this challenge, multiple imputation using chained equations, however, has been shown to be sub-optimal in complex settings, specifically in settings with longitudinal outcomes, which cannot be easily and adequately included in the imputation models. Bayesian methods avoid this difficulty by...
Paper Details
Title
Bayesian imputation of time-varying covariates in linear mixed models
Published Date
Oct 25, 2017
Volume
28
Issue
2
Pages
555 - 568
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.