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Abstract
<p>Using a cross-lagged panel model, Wan et al. interpreted their findings as evidence for reciprocal longitudinal relationships between illness-related stigma and loneliness among stroke survivors. However, estimates from cross-lagged models can reflect statistical artifacts rather than true prospective influences. In the present study, we reexamined this conclusion by fitting several alternative models to data simulated to reproduce the correlational structure reported by Wan et al. Across models, estimates varied substantially, yielding both positive and negative prospective effects between stigma and loneliness. When these divergent estimates were synthesized using meta-analytic procedures, the overall effects were not statistically distinguishable from zero. These findings suggest that the reported longitudinal effects may not represent genuine influences. Consistent with multiverse principles, we argue that conclusions should be informed by results across multiple plausible analytic specifications rather than a single modeling approach.</p>