Linear models
REGRESSION
We considered a series of Ordinary Least Squares (OLS) regression models to examine the relationship between post-dose behavior (d-prime in go-no-go blocks) as a function of different input variables (Fig. We compared the performance of the four following models:Basic model: input variables included pre-dose behavior, sex (0:female/1:male) and age of the participant (3 total variables).BAC model: direct measure of intoxication (BAC) was included as an input variable in addition to those in the basic model (4 total variables).Direction model: the direction lateralization metric was added as a variable to those in the BAC model (5 total variables)Angle model: to account for the circular nature of the angle metric, and to include this measure as a variable in our linear models, we computed the sine and cosine of the angles, multiplied by the corresponding magnitudes separately. These two variables were simultaneously included as input variables in addition to those in the BAC model (6 total variables).To control for family-wise error rate, we used a Bonferroni correction to obtain adjusted p values when comparing the four models.A separate additional model was used to investigate the role of subjective measures of intoxication.