An EM-Based Method for Q-Matrix Validation.

ABSTRACT: With the purpose to assist the subject matter experts in specifying their Q-matrices, the authors used expectation-maximization (EM)-based algorithm to investigate three alternative Q-matrix validation methods, namely, the maximum likelihood estimation (MLE), the marginal maximum likelihood estimation (MMLE), and the intersection and difference (ID) method. Their efficiency was compared, respectively, with that of the sequential EM-based δ method and its extension (ς²), the γ method, and the nonparametric method in terms of correct recovery rate, true negative rate, and true positive rate under the deterministic-inputs, noisy "and" gate (DINA) model and the reduced reparameterized unified model (rRUM). Simulation results showed that for the rRUM, the MLE performed better for low

SUBMITTER: Wang W 

PROVIDER: S-EPMC6373855 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature