ArticleJournal of the American Statistical Association2014
Mechanistic Hierarchical Gaussian Processes.
Article in Journal of the American Statistical Association, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Skeletal Muscle Quality: A Biomarker for Assessing Physical Performance Capabilities in Young Populations.Frontiers in physiology · 2021Review
- Estimation of time-varying reproduction numbers underlying epidemiological processes: A new statistical tool for the COVID-19 pandemic.PloS one · 2020Article
- An Old Problem: Aging and Skeletal-Muscle-Strain Injury.Journal of sport rehabilitation · 2017Article
- Aggregate Exposure and Cumulative Risk Assessment--Integrating Occupational and Non-occupational Risk Factors.Journal of occupational and environmental hygiene · 2015Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The statistics literature on functional data analysis focuses primarily on flexible black-box approaches, which are designed to allow individual curves to have essentially any shape while characterizing variability. Such methods typically cannot incorporate mechanistic information, which is commonly expressed in terms of differential equations. Motivated by studies of muscle activation, we propose a nonparametric Bayesian approach that takes into account mechanistic understanding of muscle physiology. A novel class of hierarchical Gaussian processes is defined that favors curves consistent with differential equations defined on motor, damper, spring systems. A Gibbs sampler is proposed to sample from the posterior distribution and applied to a study of rats exposed to non-injurious muscle activation protocols. Although motivated by muscle force data, a parallel approach can be used to include mechanistic information in broad functional data analysis applications.
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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.