Evidence map›Paper›PMID 40270260›Full record

ArticlePsychometrika2025

Show Me Some ID: A Universal Identification Program for Structural Equation Models.

Michael D Hunter, Robert M Kirkpatrick, Michael C Neale

Abstract read
In one paragraph

Article in Psychometrika, 2025. 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

3 authors.

Michael D HunterDepartment of Human Development and Family Studies Pennsylvania State University University Park, PA16802.ORCID https://orcid.org/0000-0002-3651-6709
Robert M KirkpatrickVirginia Institute for Psychiatric and Behavioral Genetics Virginia Commonwealth UniversityRichmond, VA23298.
Michael C NealeVirginia Institute for Psychiatric and Behavioral Genetics Virginia Commonwealth UniversityRichmond, VA23298.

Funding

Adolescent Substance Use Initiation: Disentangling neurocognitive risks from consequences using longitudinal and genetically-informed methodsU01DA041120 · NIDA · UNIVERSITY OF MINNESOTA · PI Monica Luciana, Sylia Wilson · 2015 to 2026
$34.5M
Extensions of Mendelian Randomization Methodology for Combined Genomic and Methylomic AnalysisR01DA049867 · NIDA · VIRGINIA COMMONWEALTH UNIVERSITY · PI NEALE, MICHAEL CHURTON · 2020 to 2024
$1.9M
NIDA NIH HHS 1R01DA049867-01A1NIDA NIH HHS R01 DA049867NIDA NIH HHS U01 DA041120
6 · The paper itself

Abstract

With models and research designs ever increasing in complexity, the foundational question of model identification is more important than ever. The determination of whether or not a model can be fit at all or fit to some particular data set is the essence of model identification. In this article, we pull from previously published work on data-independent model identification applicable to a broad set of structural equation models, and extend it further to include extremely flexible exogenous covariate effects and also to include data-dependent empirical model identification. For illustrative purposes, we apply this model identification solution to several small examples for which the answer is already known, including a real data example from the National Longitudinal Survey of Youth; however, the method applies similarly to models that are far from simple to comprehend. The solution is implemented in the open-source OpenMx package in R.

Indexed as

model identificationNational Longitudinal Survey of Youth (NLSY)structural equation model (SEM)

Identifiers

PMID40270260
PMCPMC12483695

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.