Evidence map›Paper›PMID 37661821›Full record

ArticleBiometrics2023

Latent factor model for multivariate functional data.

Ruonan Li, Luo Xiao

Abstract read
In one paragraph

Article in Biometrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Contrastive Latent Functional Model.Statistics in biosciences · 2026
    Article
  3. Article
  4. Bayesian Inference on Brain-Computer Interfaces via GLASS.Journal of the American Statistical Association · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
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.

Ruonan LiDepartment of Statistics, North Carolina State University, Raleigh, North Carolina, USA.ORCID 0000-0001-7293-9779
Luo XiaoDepartment of Statistics, North Carolina State University, Raleigh, North Carolina, USA.ORCID 0000-0001-8707-0914

Funding

Integrative modeling and dynamic prediction of Alzheimer's diseaseR01AG064803 · NIA · DUKE UNIVERSITY · PI LUO, SHENG · 2020 to 2024
$2.3M
Comprehensive White-matter Microstructure-informed Analytical Methods to Elucidate Neurobiological Mechanisms of Sports-related Concussion (SRC)R01NS112303 · NINDS · INDIANA UNIVERSITY INDIANAPOLIS · PI HAREZLAK, JAROSLAW, WU, YU-CHIEN · 2020 to 2024
$2.3M
Influence of the College Football Athletes' Cumulative Head Impact Exposure (HIE) on the mTBI incidence and post-mTBI health outcomesR01NS126449 · NINDS · TRUSTEES OF INDIANA UNIVERSITY · PI HAREZLAK, JAROSLAW, STEMPER, BRIAN D · 2022 to 2025
$1.4M
NIA NIH HHS R01 AG064803NINDS NIH HHS R01 NS112303NINDS NIH HHS R01 NS126449
6 · The paper itself

Abstract

For multivariate functional data, a functional latent factor model is proposed, extending the traditional latent factor model for multivariate data. The proposed model uses unobserved stochastic processes to induce the dependence among the different functions, and thus, for a large number of functions, may provide a more parsimonious and interpretable characterization of the otherwise complex dependencies between the functions. Sufficient conditions are provided to establish the identifiability of the proposed model. The performance of the proposed model is assessed through simulation studies and an application to electroencephalography data.

Indexed as

ElectroencephalographyModels, StatisticalComputer SimulationStochastic Processescovariance functionfPCAfunctional datamodel identifiabilitypenalized splines

Identifiers

PMID37661821
PMCPMC10840703

What OpenQuestion holds

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Registered trials

None linked

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.