TABLE 2.

The six variables of interest, including three predictors and three outputs, their primary methods of measurement, and the number of data points used to estimate each variable’s PDF.

Variable type	Variable name	Primary measure(s)	Number of data points	Marginal computation method
Predictor	Stress	Cortisol, alpha amylase, heart rate, and subjective responses	2,066	Mixture modeling + Maximum likelihood
	Sleep	Hours duration	204,403	Kernel density estimate
	Physical exertion	Borg ratings of perceived exertion	4,560	Kernel density estimate
Outcome	Reaction time	Milliseconds latency	20,973	Kernel density estimate
	Executive function	Proportion errors	5,691	Kernel density estimate
	Perceptuo-motor control	Proportion errors	8,265	Kernel density estimate