We then examined whether OPRM1 and DAT1 genotypes, alone or in interaction with each other, were associated with differences in recent alcohol consumption or subjective effects of alcohol in the CAD procedure. Drinking data was not normally distributed across the 90-day period of the TLFB. We did not use log-transformations, as these do not address the bound range (0–90) and non-drinking days (0 drinks) do not transformed properly. Instead, we constructed three generalized linear regression models (GLRM) to examine three main TLFB measures: 1) average standard drinks per drinking day, 2) number of drinking days, and 3) number of heavy drinking days (i.e., 4 or more drinks for women and 5 or more drinks for men). Assuming the probability of a participant having a drink on any given day remains the same during the 90 day period, the total number of drinking days follows a binomial distribution (e.g., non-drinking day=0, drinking day=1). The same assumption and modeling was applied to number of heavy drinking days to determine the relative risk. The number of drinks per drinking day is counting data,
