Evidence map›Paper›PMID 35419192›Full record

ArticleStat (International Statistical Institute)2021

Bayesian nonparametric multiway regression for clustered binomial data.

Eric F Lock, Dipankar Bandyopadhyay

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Stat (International Statistical Institute), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Eric F LockDivision of Biostatistics, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0003-4663-2356
Dipankar BandyopadhyayDepartment of Biostatistics, Virginia Commonwealth University, Richmond, Virginia, USA.ORCID 0000-0001-5421-1725

Funding

Virus Vector Shared ResourceP30CA016059 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI Kim Felder Rhoads · 1985 to 2026
$51.0M
UNIVERSITY OF MINNESOTA CLINICAL AND TRANSLATIONAL SCIENCE INSTITUTE (UMN CTSI)UL1RR033183 · NCRR · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R · 2011 to 2011
$8.9M
Identifying Biomarkers from Multi-source, Multi-way DataR01GM130622 · NIGMS · UNIVERSITY OF MINNESOTA · PI LOCK, ERIC F · 2019 to 2023
$1.5M
Supplement: Spatiotemporal models for periodontal disease monitoring and recall frequenciesR01DE024984 · NIDCR · VIRGINIA COMMONWEALTH UNIVERSITY · PI BANDYOPADHYAY, DIPANKAR, REICH, BRIAN J. · 2015 to 2017
$1.2M
NCI NIH HHS P30 CA016059NCRR NIH HHS UL1 RR033183NIDCR NIH HHS R01 DE024984NIGMS NIH HHS R01 GM130622
6 · The paper itself

Abstract

We introduce a Bayesian nonparametric regression model for data with multiway (tensor) structure, motivated by an application to periodontal disease (PD) data. Our outcome is the number of diseased sites measured over four different tooth types for each subject, with subject-specific covariates available as predictors. The outcomes are not well characterized by simple parametric models, so we use a nonparametric approach with a binomial likelihood wherein the latent probabilities are drawn from a mixture with an arbitrary number of components, analogous to a Dirichlet process. We use a flexible probit stick-breaking formulation for the component weights that allows for covariate dependence and clustering structure in the outcomes. The parameter space for this model is large and multiway:

Indexed as

Bayesian nonparametricsbinomial regressionDirichlet processesPARAFAC/CANDECOMPtensor factorization

Identifiers

PMID35419192
PMCPMC9004620

What OpenQuestion holds

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Registered trials

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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.