Although the generalized deterministic inputs, noisy "and" gate model (G-DINA; de la Torre, 2011) is a general cognitive diagnosis model (CDM), it does not account for the heterogeneity that is rooted from the existing latent groups in the population of examinees. To address this, this study proposes the mixture G-DINA model, a CDM that…

Sociologists increasingly face choices among competing algorithms that represent reasonable approaches to the same task, with little guidance in choosing among them. We develop a strategy that uses simulated data to identify the conditions under which different methods perform well and applies what is learned from the simulations to predict which…

In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…

A method for robust canonical discriminant analysis via two robust objective loss functions is discussed. Majorization is used at several stages in the minimization procedure to obtain a monotonically convergent algorithm. A simulation study and empirical data illustrate the procedure. (SLD)

This paper proposes a new Information-Time index as the basis for item selection in computerized classification testing (CCT) and investigates how this new item selection algorithm can help improve test efficiency for item pools with mixed item types. It also investigates how practical constraints such as item exposure rate control, test…