ArticleThe annals of applied statistics2020
A Global-Local Approach for Detecting Hotspots in Multiple-Response Regression.
Article in The annals of applied statistics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- A modeling framework for detecting and leveraging node-level information in Bayesian network inference.Biostatistics (Oxford, England) · 2025Article
- A computationally efficient Bayesian seemingly unrelated regressions model for high-dimensional quantitative trait loci discovery.Journal of the Royal Statistical Society. Series C, Applied statistics · 2021Article
- EPISPOT: An epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies.American journal of human genetics · 2021Article
- Bayesian Variable Selection for Gaussian copula regression models.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2020Article
- Article
- A Global-Local Approach for Detecting Hotspots in Multiple-Response Regression.The annals of applied statistics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting
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Identifiers
What OpenQuestion holds
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.