Alternative quantitative methods in psycholinguistics: Implications for theory and design
Jacolien van Rij, Nemanja Vaci, Lee H. Wurm, Laurie Beth Feldman
Abstract
We describe three different methods that are appropriate to analyze various types of psycholinguistic data. We discuss some of the strengths and weaknesses of each and their suitability according to characteristics of the data. Methods include analysis of variance (ANOVA), linear mixed-effects modeling (LME) and generalized additive mixed models (GAMM).
Topics & Concepts
PsycholinguisticsStrengths and weaknessesVariance (accounting)Computer scienceAnalysis of varianceMixed modelVariance componentsGeneralized linear mixed modelStatisticsMathematicsPsychologyMachine learningSocial psychologyCognitionBusinessNeuroscienceAccountingNatural Language Processing TechniquesCategorization, perception, and languageLinguistic Variation and Morphology