Using Latent Variable Analysis to Capture Variability in Bilingual Language Experience

Bilingualism is a fluid, multicomponent experience that varies across a continuum and can change across the lifespan. Psychometric research on the bilingual experience is an underexplored avenue with the potential to further our understanding of bilingual variability. Here, we developed and validated a social network questionnaire to measure variability in the language experience of 212 individuals and their personal social networks. Two confirmatory factor analysis models were compared. The best fitting model was a two-factor model in which the language experience of the individual (i.e., ego) and the language experience of their network (i.e., alters) were correlated latent factors under which aspects of the bilingual experience loaded. These results provide the first latent model of bilingual experience, and support the use of social network tools to measure variability in language experience, overall suggesting that bilingualism is influenced by a multiplicity of factors that varies within and across individuals.