Award-Winning Presentation at Virtual MathPsych 2022! 🏆
I’m thrilled to share that my talk at the 2022 Virtual Mathematical Psychology conference received the People’s Choice Award! This recognition from the mathematical psychology community means a lot to me, especially given this was my first conference presentation as a graduate student.
Research Overview
My presentation, titled “Principal-Component exploration of individual differences in the general-speed component of response times,” explored the structure of individual differences in response times across cognitive tasks.
Working with my advisors Jeffrey N. Rouder and Joachim Vandekerckhove, we challenged the traditional interpretation of difference scores in cognitive tasks. While these scores are commonly used to measure specific cognitive processes (like inhibition in the Stroop task), we found that:
Difference scores correlate weakly across tasks (often below 0.1)
Overall response times show strong correlations (above 0.5)
Principal Component Analysis reveals a robust general speed factor
This general speed factor is remarkably unidimensional, even compared to human anthropometrics
Watch the Talk
You can watch my presentation here:
Click to see abstract
A common method to localize cognitive processes is Donders' subtractive method. For example, to localize inhibition in the Stroop task, performance in a congruent condition is subtracted from that in an incongruent condition. Many cognitive tasks purport to measure inhibition this way. A critical question is whether individual difference scores correlate across these tasks. We find that they do not. Inhibition response time difference scores correlate weakly at best, often below .1 in value.
We revisit three large-scale data sets and find that overall task response times do correlate at over .5 in value. This result implies that participants are consistently fast or slow to respond across these tasks. The main source of individual variation is not inhibition, but rather overall or general speed.
We explore the dimensionality and structure of general speed across individuals and tasks in extended data sets. With several tasks per set, it is possible to ask whether there is a unified general speed versus several varieties of general speed. A principal component analysis (PCA) revealed a strong first factor in all sets, consistent with a unidimensional, unified construct of general speed.
One way of contextualizing these results is to compare them to human anthropometrics. While human bodies are similar in many ways, they seemingly vary on a "size" factor. We analyze a publicly available set of 93 body measurements collected across 6,068 US military personnel. Indeed, a strong first factor of size emerges, but so does a second factor that captures how heavy people are for their height. Perhaps surprisingly, the first-factor solution for general speed is comparable to or even stronger than it is for anthropometrics. Moreover, we were unable to identify a coherent second factor for general speed. We conclude that general speed is likely unidimensional.
