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A companion paper introduced the rERP framework, which recasts traditional event‐related potential (ERP) averaging as a special case of a more flexible regression‐based approach to estimating ERP waveforms. Here, we build on this foundation, showing how rERP analysis can also handle the estimation of nonlinear effects (a generalization of both the well‐known approach of dichotomizing continuous covariates,...
ERP averaging is an extraordinarily successful method, but can only be applied to a limited range of experimental designs. We introduce the regression‐based rERP framework, which extends ERP averaging to handle arbitrary combinations of categorical and continuous covariates, partial confounding, nonlinear effects, and overlapping responses to distinct events, all within a single unified system. rERPs...
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