  A new method, with an application program in Matlab code, is proposed for
testing item performance models on empirical databases. This method uses data
intraclass correlation statistics as expected correlations to which one
compares simple functions of correlations between model predictions and
observed item performance. The method rests on a data population model whose
validity for the considered data is suitably tested, and has been verified for
three behavioural measure databases. Contrarily to usual model selection
criteria, this method provides an effective way of testing under-fitting and
over-fitting, answering the usually neglected question "does this model
suitably account for these data?"
