An Alternative Approach to Cognitive and Achievement Relations Research: An Introduction to Quantile Regression | SpringerLink
https://link.springer.com/article/10.1007/s40817-020-00086-3
An Alternative Approach to Cognitive and Achievement Relations Research: An Introduction to Quantile Regression
• Daniel B. Hajovsky, Ethan F. Villeneuve, W. Joel Schneider & Jacqueline M. Caemmerer
• Journal of Pediatric Neuropsychology (2020)Cite this article
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Abstract
A large body of prior work shows that cognitive abilities and basic academic skills explain individual differences in performance on reading, writing, and math achievement measures. However, this research focuses exclusively on the average relations between cognitive and achievement scores without consideration of whether effects vary at different thresholds of academic performance. To address this limitation, we employed unconditional quantile regression to explore the effects of cognitive abilities and basic and intermediate academic skills on advanced achievement outcomes as a function of reading, writing, or math skill level in a large nationally representative sample of youth and adolescent children (N = 3891). Quantile regression is a methodological technique that allows for a more nuanced examination of whether differential effects along the distribution of an outcome skill exist, which often goes undetected when employing more conventional regression methods that focus on mean effects. Findings from this exploratory study generally showed that cognitive abilities and basic and intermediate academic skills had a pattern of differential effects depending on achievement level, with stronger effects often observed when performance on the academic outcome measure was lower. This exploratory study provides an illustrative example of unconditional quantile regression and how it can be interpreted and applied within an area of relevance to pediatric neuropsychology.
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Kevin S. McGrew, PhD
Educational & School Psychologist
Director
Institute for Applied Psychometrics (IAP)
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