ReviewEuropean journal of investigation in health, psychology and education2025
Latent Variable Statistical Methods for Longitudinal Studies of Multi-Dimensional Health and Education Data: A Scoping Review.
Review in European journal of investigation in health, psychology and education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
(1) Background: Most studies including health data have relied on reducing all variables to manifest scores, ignoring the latent nature of variables. Moreover, relying only on manifest variables is a limitation of longitudinal studies where identical measures cannot be collected at each time point. (2) Objective: This scoping review aims to identify latent variable statistical methods for longitudinal studies of multi-dimensional health and educational data investigating early health predictors of long-term educational outcomes and developmental trajectories that lead to better or worse than expected outcomes. (3) Eligibility criteria: We included peer-reviewed health and education journal articles, doctoral theses, and book chapters of longitudinal studies of children under 12 years of age that adopted latent variable, multivariate analysis of three or more waves of data. We only included full-text-available, English-written articles, without restriction on date of publication. (4) Sources of evidence: We searched five databases, Scopus, MEDLINE, PsycINFO, ERIC, and Web of Science, and identified 4836 publications for screening. (5) Results: After title, abstract, and full-text screening, nine studies were included in the review, reporting seven statistical methods. These methods were categorised into two groups-variable-oriented modelling and person-oriented modelling. (6) Conclusions: Variable-oriented modelling methods are useful for determining predictors of long-term educational outcomes. Person-oriented modelling methods are effective in detecting trajectories to better or worse than expected outcomes. (7) Registration: Open Science Framework.
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Registered trials
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 Socratic graph.