Evidence map›Paper›PMID 31631222›Full record

ArticleBiostatistics (Oxford, England)2021

A functional mixed model for scalar on function regression with application to a functional MRI study.

Wanying Ma, Luo Xiao, Bowen Liu, Martin A Lindquist

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biostatistics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Wanying MaDepartment of Statistics, North Carolina State University, 2311 Stinson Drive, Raleigh, NC 27606, USA.
Luo XiaoDepartment of Statistics, North Carolina State University, 2311 Stinson Drive, Raleigh, NC 27606, USA.
Bowen LiuDepartment of Statistics, North Carolina State University, 2311 Stinson Drive, Raleigh, NC 27606, USA.
Martin A LindquistDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA.

Funding

Individualized spatial topology in functional neuroimagingR01EB026549 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI Abhirup Datta, Martin Lindquist · 2018 to 2026
$4.5M
Longitudinal Causal Inferencer for fMRIR01EB016061 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI LINDQUIST, MARTIN · 2013 to 2020
$2.3M
Statistical Methods for Clinical Trials with Multivariate Longitudinal OutcomesR01NS091307 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI LUO, SHENG · 2015 to 2018
$1.2M
Integrative modeling and dynamic prediction of Alzheimer's diseaseR56AG064803 · NIA · DUKE UNIVERSITY · PI LUO, SHENG · 2019 to 2019
$483k
National Institute of Health R01EB016061NIA NIH HHS R56 AG064803NIBIB NIH HHS R01 EB016061NIBIB NIH HHS R01 EB026549NINDS NIH HHS R01 NS091307
6 · The paper itself

Abstract

Motivated by a functional magnetic resonance imaging (fMRI) study, we propose a new functional mixed model for scalar on function regression. The model extends the standard scalar on function regression for repeated outcomes by incorporating subject-specific random functional effects. Using functional principal component analysis, the new model can be reformulated as a mixed effects model and thus easily fit. A test is also proposed to assess the existence of the subject-specific random functional effects. We evaluate the performance of the model and test via a simulation study, as well as on data from the motivating fMRI study of thermal pain. The data application indicates significant subject-specific effects of the human brain hemodynamics related to pain and provides insights on how the effects might differ across subjects.

Indexed as

BrainMagnetic Resonance ImagingComputer SimulationHumansPrincipal Component AnalysisfMRIFunctional data analysisFunctional mixed modelFunctional principal componentRepeated measurementsVariance component testing

Identifiers

PMID31631222
PMCPMC8286587

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.