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Abstract:
The relationship between lexical and grammatical knowledge in young children is
impressively strong. Indeed, the correlation between productive vocabulary and
grammar (r = .84) is larger than that between productive and receptive vocabulary (r =
.63) when measured with the commonly used Communicative Development
Inventories (CDIs). This correlation fits cleanly with usage-based theories of language,
which assume no clear distinction between the lexicon and grammar (Tomasello,
2003). However, it could also reflect separate systems that are mutually causally
related (mutualism); initially uncorrelated domains can gradually become so correlated
as to be statistically indistinguishable when they are mutually causally related (Van der
Maas et al 2006). Disentangling these accounts is complicated by the non-linear
relationship between true and measured grammatical/lexical knowledge, which is not
accounted for in traditional regression-based approaches. Here we present a new
approach to disentangling these accounts which overcomes these measurement
challenges. We examined the dimensional structure of item-level data from CDI data
on Wordbank (Frank et al. 2017) using item-response theory and the DETECT method
(Stout et al. 1996). We first considered all non-longitudinal data from the American
English subsample of Wordbank. A DETECT analysis found evidence of moderate
multidimensionality with vocabulary and grammar items clustering separately, contra
some usage-based accounts which assume no distinction between grammatical and
lexical knowledge. Given that mutualism predicts that two domains become
increasingly correlated with age, we next ran a similar analysis in separate sets of
younger (~18 months) and older (~28 months) children. These data were
unidimensional at 18 months and multidimensional at 28 months. In sum, our results did not strongly support either account described above and are most consistent with
an initially integrated lexico-grammatical system that becomes decoupled between the second and third year.
