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Vortrag von R. Harald Baayen am Freitag,16.01.2015 (10:00 Uhr - GB 3/159)

Freitag, 28. November 2014. Aus der Kategorie 'Vortragsreihe'. Das Sprachwissenschaftliche Institut lädt ein zum Vortrag von

R. Harald Baayen (Tübingen):
Generalized Additive Mixed Models


Generalized additive mixed models (GAMMs) are an extension of the generalized linear mixed model that provides the analyst with a wide range of tools to model nonlinear functional dependencies in two or more dimensions (wiggly regression curves, wiggly regression surfaces and hypersurfaces). GAMMs, which are implemented in the mgcv package for R by Simon Wood, provide a substantial and non-trivial addition to the toolkit of experimental psychology and experimental linguistics. One particularly important extension is the possibility to include random effect factor smooths. In the context of the classic linear mixed-effects model, random intercepts combined with random slopes make it possible to calibrate regression lines to the levels of random effect factors (e.g., subjects). The factor smooths in GAMMs provide a non-linear extension, enabling the modeling of nonlinear curves instead of straight lines. GAMMs can be important for capturing nonlinear trends in time series data, ranging from the successive reaction times in a simple behavioral experiment to the subject-specific fluctuations in the amplitude of the electrophysiological response of the brain to items in an EEG experiment. GAMMs are also crucial for the proper modeling of nonlinear interactions between numerical predictors. The potential of GAMMs for the language sciences will be illustrated by means of examples from dialectometry, phonetics, and psycholinguistics.