The effect of alcohol hangover on cognitive processing has received little attention. We explored the effect of alcohol hangover on choice response time (RT), a dominant dependent variable (DV) in cognitive research. Prior research of the effect of hangover on RT has produced mixed findings; all studies reviewed relied exclusively on estimates of central tendency (e.g. mean RT), which has limited information value. Here we present novel analytical methods by going beyond mean RT analysis. Specifically, we examined performance in hangover conditions (n=31) across the whole RT distribution by fitting ex-Gaussian models to participant data, providing a formal description of the RT distribution. This analysis showed detriments to performance under hangover conditions at the slower end of the RT distribution and increased RT variance under hangover conditions. We also fitted an explicit mathematical process model of choice RT - the diffusion model - which estimates parameters reflecting psychologically-meaningful processes underlying choice RT. This analysis showed that hangover reduced information processing efficiency during response selection, and increased response caution; changes in these parameters reflect hangover affecting core decisional-components of RT performance. The implications of the data as well as the methods used for hangover research are discussed.