Visual World Paradigm Data: From Preprocessing to Nonlinear Time-Course Analysis

Vince Porretta, Aki-Juhani Kyröläinen, Jacolien van Rij, Juhani Järvikivi

OnderzoeksoutputAcademicpeer review

11 Citaten (Scopus)

Samenvatting

Abstract. The Visual World Paradigm (VWP) is used to study online spoken language processing and produces time-series data. The data present challenges for analysis and they require significant preprocessing and are by nature nonlinear. Here, we discuss VWPre, a new tool for data preprocessing, and generalized additive mixed modeling (GAMM), a relatively new approach for nonlinear time- series analysis (using mgcv and itsadug), which are all available in R. An example application of GAMM using preprocessed data is provided to illustrate its advan‐ tages in addressing the issues inherent to other methods, allowing researchers to more fully understand and interpret VWP data.
Originele taal-2English
TitelIntelligent Decision Technologies 2017
RedacteurenIreneusz Czarnowski, Robert J. Howlett, Lakhmi C. Jain
Plaats van productieCham, Switzerland
UitgeverijSpringer International Publishing AG
Pagina's268-277
ISBN van elektronische versie978-3-319-59424-8
ISBN van geprinte versie978-3-319-59423-1
DOI's
StatusPublished - 2017

Publicatie series

NaamSmart Innovation, Systems and Technologies
UitgeverijSpringer International Publishing AG
Volume73
ISSN van geprinte versie2190-3018
ISSN van elektronische versie2190-3026

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