Exploiting random intercepts: Two case studies in sociophonetics

Abstract An increasing number of sociolinguists are using mixed effects models, models which allow for the inclusion of both fixed and random predicting variables. In most analyses, random effect intercepts are treated as a by-product of the model; they are viewed simply as a way to fit a more accurate model. This paper presents additional uses for random effect intercepts within the context of two case studies. Specifically, this paper demonstrates how random intercepts can be exploited to assist studies of speaker style and identity and to normalize for vocal tract size within certain linguistic environments. We argue that, in addition to adopting mixed effect modeling more generally, sociolinguists should view random intercepts as a potential tool during analysis.