A Quantitative Reanalysis of Data on the Structure of L1 and L2 Language Ability in Multitrait-Multimethod Studies
A Quantitative Reanalysis of Data on the Structure of L1 and L2 Language Ability in Multitrait-Multimethod Studies
Keywords: multitrait multimethod, language ability structure, confirmatory factor analysis, first language, second language
Yo In’nami and Rie Koizumi
Shibaura Institute of Technology
Juntendo University, Japan
Bio Data
Yo In’nami Ph.D. is an Associate Professor of English in the College of Engineering at Shibaura Institute of Technology, Japan. He is interested in meta-analytic inquiry into the variability of effects and the longitudinal measurement of change in language proficiency.
Rie Koizumi Ph.D. is an Associate Professor of English in the Faculty of Medicine at Juntendo University, Japan. She is interested in validating speaking and vocabulary assessment and modeling factor structures of language ability and performance.
To gain a better understanding of the structure of L1 and L2 language ability, we conducted an extensive literature search to collect multitrait-multimethod (MTMM) studies. We specifically examined the unitary, correlated, uncorrelated, and higher-order structures of language ability to determine which of these best fit the data across studies. We used confirmatory factor analysis to reanalyze 58 correlation or covariance matrices from 39 studies, among which we retained 17 correlation or covariance matrices from 14 studies for the main analysis. Empirical evidence showed that the unitary and higher-order models best defined both L1 and L2 ability. The support for the unitary model was surprising but consistent with the findings of Davidson (1988). Moderator variable analyses failed to identify clear relationships between the examined models and moderator variables.
Category: Main Editions, Volume 14 Issue 3
