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A cross-sectional exploration of cognitive ability across age via stacked ensembles.

Published in Psychology and Aging, 2024

This study uses machine learning on data from 750,000 participants to model how cognitive performance from ages 25 to 80 varies by age, gender, and education. It reveals nuanced demographic patterns—such as gender gaps narrowing with age and education-specific differences in fluid reasoning—highlighting the complexity of cognitive aging.

Recommended citation: Congdon, E. L., Liu, S., & Upton, E. M. (2025). A cross-sectional exploration of cognitive ability across age via stacked ensembles. Psychology and Aging, 40(2), 159–177. https://doi.org/10.1037/pag0000868

Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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