Categorization and validation of handedness using latent class analysis

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    Abstract

    [truncated abstract] Background: A view that handedness is not a dichotomous, i.e. left-right, phenomenon is shared by majority of researchers. However, there are different opinions about the exact number of hand-preference categories and criteria that should be used for their classification.Objectives: This study examined hand-preference categories using the latent class analysis (LCA) and validated them against two external criteria (i.e. hand demonstration test and a series of arbitrary cut-off points).Method: The Edinburgh Handedness Inventory was applied to 354 individuals randomly selected from the general population, and the obtained data were analysed using the LatentGOLD software.Results: Three discrete hand-preference clusters were identified, i.e. left-, right- and mixed-handed category. Further subdivision of hand-preference clusters resulted in a non-parsimonious subcategorization of individuals. There was a good agreement between the LCA-based classification and classification based on hand-preference demonstration tests. The highest agreement between the LCA model and the different types of arbitrary classification criteria ranged between 0 +/- 50 and 0 +/- 70 of the laterality quotient.Conclusions: The study findings supported the view that handedness is not a bimodal phenomenon. However, definitions and subcategorizations of mixed-handedness using the cut-off points that are outside of the recommended range may lead to misclassification of cases...
    Original languageEnglish
    Pages (from-to)212-218
    JournalActa Neuropsychiatrica
    Volume16
    Issue number4
    DOIs
    Publication statusPublished - 2004

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