Inconclusive mutually reinforcing effects between associative learning and fluid intelligence: simulated reanalyses...

Based on findings from analyses with the random-intercept cross-lagged panel model (RI-CLPM), Ren et al. concluded reinforcing longitudinal effects between associative learning and fluid intelligence. However, the RI-CLPM is susceptible to spurious findings. Here, we analyzed data simulated to resemble the data used by Ren et al. with alternative models and found discrepant increasing, decreasing, and null prospective effects between associative learning and fluid intelligence. Hence, the conclusions by Ren et al. appear not to be supported by their own data. It is important for researchers to bear in mind that correlations, including effects in the RI-CLPM, in observational (i.e., non-experimental) data may be spurious and do, consequently, not prove genuine (i.e., non-spurious) influence. We recommend researchers to fit alternative models to data and to base conclusions on an aggregation of findings.