Assessment of handedness using latent class factor analysis

Recently several studies in which handedness was evaluated as a latent construct have been performed. In those studies, handedness was modelled using a qualitative latent variable (latent class models), a continuous latent variable (factor models), or both a qualitative latent variable and a continuous latent trait (mixed Rasch models). The aim of this study was to explore the usefulness and effectiveness of an approach in which handedness is treated as a qualitatively scaled latent variable with ordered categories (latent class factor models). This aim was pursued through an exploratory analysis of a dataset containing information on the hand used by 2236 young Italian sportspeople to perform 10 tasks. For comparison purposes, a latent class analysis was carried out. A cross-validation procedure was implemented. The results of all the analyses revealed that the best fit to the observed handedness patterns was obtained using a latent class factor model. Through this model, individuals were assigned to one of four ordered levels of handedness, and a quantitative index of left-handedness for each individual was computed by taking into account the different effect of the 10 tasks. These results provide support for the use of the latent class factor approach for handedness assessment.