ArticleBiostatistics (Oxford, England)2022
Fast approximate inference for multivariate longitudinal data.
Article in Biostatistics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- A fast integrative clustering and feature selection approach for high-dimensional multiview data.Statistical methods in medical research · 2026Article
- Multi-response phylogenetic mixed models: concepts and application.Biological reviews of the Cambridge Philosophical Society · 2025Review
- Fast and flexible inference for joint models of multivariate longitudinal and survival data using integrated nested Laplace approximations.Biostatistics (Oxford, England) · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Collecting information on multiple longitudinal outcomes is increasingly common in many clinical settings. In many cases, it is desirable to model these outcomes jointly. However, in large data sets, with many outcomes, computational burden often prevents the simultaneous modeling of multiple outcomes within a single model. We develop a mean field variational Bayes algorithm, to jointly model multiple Gaussian, Poisson, or binary longitudinal markers within a multivariate generalized linear mixed model. Through simulation studies and clinical applications (in the fields of sight threatening diabetic retinopathy and primary biliary cirrhosis), we demonstrate substantial computational savings of our approximate approach when compared to a standard Markov Chain Monte Carlo, while maintaining good levels of accuracy of model parameters.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.