Latent Variable Modelling and Item Response Theory Analyses in Marketing Research
Publié en ligne: 04 avr. 2017
Pages: 163 - 174
Reçu: 06 mars 2016
Accepté: 06 oct. 2016
DOI: https://doi.org/10.1515/foli-2016-0032
Mots clés
© 2016 University of Szczecin
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Item Response Theory (IRT) is a modern statistical method using latent variables designed to model the interaction between a subject’s ability and the item level stimuli (difficulty, guessing). Item responses are treated as the outcome (dependent) variables, and the examinee’s ability and the items’ characteristics are the latent predictor (independent) variables. IRT models the relationship between a respondent’s trait (ability, attitude) and the pattern of item responses. Thus, the estimation of individual latent traits can differ even for two individuals with the same total scores. IRT scores can yield additional benefits and this will be discussed in detail. In this paper theory and application with R software with the use of packages designed for modelling IRT will be presented.