Growth models show substantial variability in the shape and rate of learning, but no statistically significant EAPGS associations with that variation¶

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2022 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Fitting linear, logarithmic, and exponential growth models with EAPGS as a predictor of random-effect parameters revealed substantial individual variability in shape and rate of learning but no statistically significant EAPGS associations. → Cherry Youn 2022

Evidence¶

Cherry Youn 2022¶

Cherry Youn, Andrew D. Grotzinger, Christina M. Lill, Lars Bertram, Florian Schmiedek, Martin Lövdén, Ulman Lindenberger, Michel Nivard, K. Paige Harden, Elliot M. Tucker-Drob. (2022). Genetic associations with learning over 100 days of practice. npj Science of Learning. https://doi.org/10.1038/s41539-022-00121-2

q2 · i? · associational · r2

Nonlinear growth curve models (NLMIXED in SAS) fitted to cognitive performance across 100 days for 131 participants, with EAPGS entered as a predictor of all random-effect parameters. The article reports "no statistically significant associations between the EAPGS and this variation".

"Results indicated substantial variability in the shape and rate of learning. However, there were no statistically significant associations between the EAPGS and this variation."

Discussion¶

Related Claims¶

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