Table 4.

Reaction time model for food choices

Fixed effects	Beta estimate	Standard deviation	95% highest density interval
Intercept	0.15	0.03	[0.09; 0.20]
Yes (to HTHH)	-0.07	0.03	[−0.12; −0.02]
HTLH	-0.05	0.02	[−0.09; −0.01]
LTHH	0.03	0.02	[−0.02; 0.07]
Stakes	0.00	0.01	[−0.03; 0.03]
Difficulty	0.10	0.03	[0.05; 0.15]
Yes × HTLH	0.24	0.05	[0.15; 0.33]
Yes × LTHH	0.26	0.05	[0.17; 0.36]
Bayesian R2	0.27	0.01	[0.25; 0.29]

This table reports the results from the Bayesian regression model of RTs for food choices specified in equation (4). RTs were transformed using the natural logarithm. The variable Yes was coded with a value of 1 if participants chose to eat the depicted item and 0 otherwise. Trial type was coded as a factor with three categories (non-challenging high-taste/high-health (HTHH) and low-taste/low-health (LTLH) trials as the reference category, and high-taste/low-health (HTLH) trials and low-taste/high-health (LTHH) trials as indicator variables). The variable stakes was calculated for each trial as described in equation (5) and the variable difficulty was calculated for each trial as described in equation (6). The regression included participant-specific intercepts and participant-specific random slopes for all regressors and interaction terms. The coefficients (beta estimates) listed are the means of the population level posterior distributions ± SD and the 95% highest density interval. The analysis comprised N = 38 participants.