I'm planning a study using Structural Equation Modelling to test different accounts of language learning. I would like to study a group of children with language difficulties. However, they are very hard to recruit and I'm aware that these models typically require at least 200 participants. One possibility would be
(1) Test SEMs on a large cohort of typically developing children - who are much easier to recruit (n = 500). (NB I'm imagining 3 or 4 different models each with about 3 or 4 latent variables).
(2) Apply these models to a smaller cohort of language impaired individuals (n = 80)
I'm imagining that in the second stage one would keep the coefficients from stage one, and would use some kind of procedure to manipulate the values of the latent (exogenous) variables to maximise model fit. Research questions would be
- Which model best describes the data for the typically developing children?
- Does this model also best describe the data for the language impaired children?
I'm wondering if this is statistically feasible and whether anyone has tried this approach before. Ta.