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Using triangulation to evaluate findings from random-intercept cross-lagged panel models: An application with data on
1Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Plos One
|December 4, 2025
Summary
Longitudinal associations between curiosity and creativity may be spurious, not mutually reinforcing. Further analysis using multiple models suggests confounding factors, challenging previous findings from the random-intercept cross-lagged panel model (RI-CLPM).
Area of Science:
- Psychology
- Cognitive Science
- Quantitative Psychology
Background:
- Previous research using the random-intercept cross-lagged panel model (RI-CLPM) suggested mutual reinforcement between curiosity and creativity.
- Concerns exist regarding potential biases and limitations of the RI-CLPM in capturing true longitudinal effects.
Purpose of the Study:
- To re-evaluate the relationship between curiosity and creativity using triangulation with multiple statistical models.
- To investigate whether the previously reported mutually reinforcing effects are robust or potentially spurious.
Main Methods:
- Analysis of existing data (N=400) using a latent change score model (LCSM) and multilevel regression analyses.
- Comparison of results from RI-CLPM with those from LCSM, multilevel regression, and the model of spurious longitudinal associations (MoSLA).
Main Results:
- Results from LCSM and multilevel regression contradicted the RI-CLPM findings, indicating no mutual reinforcement.
- The MoSLA suggested that the observed longitudinal associations might be spurious, potentially due to confounding variables.
- Only the RI-CLPM analysis supported the conclusion of mutually reinforcing effects.
Conclusions:
- The longitudinal associations between curiosity and creativity in this dataset are likely spurious, not indicative of a direct causal or mutually reinforcing relationship.
- Confounding factors, such as shared traits or state effects, may explain the observed correlations.
- The study provides a methodological tutorial for scrutinizing RI-CLPM results and highlights the importance of employing multiple analytical approaches.
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