The 'deterministic‐input noisy‐AND'(DINA) model is one of the more frequently applied
diagnostic classification models for binary observed responses and binary latent variables …

The assumption of conditional independence between the responses and the response
times (RTs) for a given person is common in RT modeling. However, when the speed of a …

The paper offers a general review of the basic concepts of both statistical model and
parameter identification, and revisits the conceptual relationships between parameter …

With a few exceptions, the problem of linking item response model parameters from different
item calibrations has been conceptualized as an instance of the problem of test equating …

In this paper, we study the identification of a particular case of the 3PL model, namely when
the discrimination parameters are all constant and equal to 1. We term this model, 1PL-G …

In behavioral, biomedical, and psychological studies, structural equation models (SEMs)
have been widely used for assessing relationships between latent variables. Regression …

Why identification is relevant for model construction? In 1922, RA Fisher pointed out that, in
spite of the large amount of fruitful applications of statistics, its basic principles were still in a …

In modern Item Response Theory, the Rasch model is viewed as a Generalized Linear
Mixed Model, where the item parameters correspond to the fixed-effects, whereas the …

Item response theory (IRT) models typically rely on a normality assumption for subject-
specific latent traits, which is often unrealistic in practice. Semiparametric extensions based …

In the past 2 decades latent variable modeling has become a standard tool in the social
sciences. In the same time period, traditional linear structural equation models have been …