Working memory predicts GPA in the initial model but not the final full-sample model¶

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2017 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Working memory was significant in the initial genetic-subgroup regression (β = 0.192, p = 0.028) but was no longer significantly predictive in the final full-sample model (β = 0.109, p = 0.055). → Imlach 2017

Evidence¶

Imlach 2017¶

Imlach, A.-R., Ward, D. D., Stuart, K. E., Summers, M. J., Valenzuela, M. J., King, A. E., Saunders, N. L., Summers, J., Srikanth, V. K., Robinson, A. & Vickers, J. C. (2017). Age is no barrier: predictors of academic success in older learners. npj Science of Learning 2:13. https://doi.org/10.1038/s41539-017-0014-5

q2 · i? · associational · r2

In the initial regression (N = 181), working memory was a significant primary predictor (β = 0.192, p = 0.028). After re-examination in the full sample (N = 329) with secondary predictors added, its effect fell to β = 0.109, p = 0.055. The effect therefore does not replicate across models.

"The predictive capacity of the model increased by 2.3% of the variance in GPA due to the inclusion of secondary predictors, and working memory was no longer significantly predictive."

Discussion¶

Related Claims¶

• Age is not associated with academic performance (GPA) in older learners up to the eighth decade — related
• Language processing and episodic memory predict first-year GPA in older university learners — related
• Candidate gene polymorphisms (APOE, BDNF, COMT, KIBRA, SERT) are not associated with GPA in older learners — related
• Full-scale IQ does not predict GPA in older learners — related
• Years of prior education significantly predict GPA in older learners — related
• Previous domain knowledge accounts for most of the variance in later achievement, considerably reducing the predictive impact of IQ and WM — related