TY - GEN
T1 - Visual World Paradigm Data
T2 - From Preprocessing to Nonlinear Time-Course Analysis
AU - Porretta, Vince
AU - Kyröläinen, Aki-Juhani
AU - van Rij, Jacolien
AU - Järvikivi, Juhani
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
U2 - 10.1007/978-3-319-59424-8_25
DO - 10.1007/978-3-319-59424-8_25
M3 - Conference contribution
SN - 978-3-319-59423-1
T3 - Smart Innovation, Systems and Technologies
SP - 268
EP - 277
BT - Intelligent Decision Technologies 2017
A2 - Czarnowski, Ireneusz
A2 - Howlett, Robert J.
A2 - Jain, Lakhmi C.
PB - Springer International Publishing AG
CY - Cham, Switzerland
ER -