ArticlePloS one2026
Spurious effects in random-intercept cross-lagged panel models: Results from simulations and reanalyses of data on self-esteem and problematic eating behaviors used by Beckers et al. (2023).
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Commentary: The longitudinal impact of emotional intelligence and psychological empowerment on work engagement among university administrators: a cross-lagged panel model approach.Frontiers in psychology · 2026Article
- Loneliness and functional limitations shaping one another: evidence from the Health and Retirement Study.Aging & mental health · 2025Article
- Meta-analytic prospective associations between self-esteem and eating disorders appear to be spurious: a reanalysis and comment on Krauss et al. (2023).Frontiers in psychology · 2025Article
- Inconclusive effects between executive functions and symptoms of psychiatric disorders in random-intercept cross-lagged panel models: a simulated reanalysis and comment on Halse et al. (2022).Frontiers in psychology · 2025Article
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The random-intercept cross-lagged panel model (RI-CLPM) is an extension of the traditional cross-lagged panel model. The RI-CPLM specifically addresses prospective effects within individuals. In the present simulations, we found that the RI-CLPM is susceptible to spurious findings when observed scores on the two variables are affected by common auto-correlated state factors. In reanalyses of empirical data, we found contradictory decreasing, increasing, and null prospective effects between within-individual levels of self-esteem and problematic eating behaviors among Dutch teenagers (N = 1856). These contradictory findings indicated that previously reported prospective effects may have been statistical artifacts. Caution is advised when using the RI-CLPM, as it may produce misleading results. Researchers are recommended to validate findings using alternative analyses, e.g., by examining person-mean centered scores.
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Registered trials
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