An introduction to Generalized Additive Mixed Models
Generalized additive models are an extension of regression that provides the user with flexible tools to modeling nonlinear functional relations between the response variable and one or more numeric predictors, where required in interaction with factorial predictors. Following examples of applications of phonetics and in dialectometry, I will focus on applications of GAMs in psycholinguistics (analysis of response latencies, analysis of EEG data).