Evidence map›Paper›PMID 29497368›Full record

ReviewFrontiers in behavioral neuroscience2018

Meta-Analysis of the Structural Equation Models' Parameters for the Estimation of Brain Connectivity with

Joan Guàrdia-Olmos, Maribel Peró-Cebollero, Esteve Gudayol-Ferré

Abstract readReview
In one paragraph

Review in Frontiers in behavioral neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Structural equation modeling of findings in pediatric tele-neuroradiology: a 2-year nationwide study of turnaround time predictors and clinical decision support.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2026
    Article
  2. Article
  3. 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

3 authors.

Joan Guàrdia-OlmosDepartment of Social Psychology and Quantitative Psychology, School of Psychology, Institute of Neuroscience, Institute of Complexity, University of Barcelona, Barcelona, Spain.
Maribel Peró-CebolleroDepartment of Social Psychology and Quantitative Psychology, School of Psychology, Institute of Neuroscience, Institute of Complexity, University of Barcelona, Barcelona, Spain.
Esteve Gudayol-FerréSchool of Psychology, Universidad Michoacana de San Nicolás de Hidalgo de Morelia, Morelia, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Structural Equation Models (SEM) is among of the most extensively applied statistical techniques in the study of human behavior in the fields of Neuroscience and Cognitive Neuroscience. This paper reviews the application of SEM to estimate functional and effective connectivity models in work published since 2001. The articles analyzed were compiled from Journal Citation Reports, PsycInfo, Pubmed, and Scopus, after searching with the following keywords: fMRI, SEMs, and Connectivity.

Indexed as

cognitive neuroscienceeffective connectivityfMRIfunctional connectivitystructural equation models

Identifiers

PMID29497368
PMCPMC5818469

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.