title: Limited information estimation of the diffusion-based item response theory model for responses and response times.
abstract: Psychological tests are usually analysed with item response models. Recently, some alternative measurement models have been proposed that were derived from cognitive process models developed in experimental psychology. These models consider the responses but also the response times of the test takers. Two such models are the Q-diffusion model and the D-diffusion model. Both models can be calibrated with the diffIRT package of the R statistical environment via marginal maximum likelihood (MML) estimation. In this manuscript, an alternative approach to model calibration is proposed. The approach is based on weighted least squares estimation and parallels the standard estimation approach in structural equation modelling. Estimates are determined by minimizing the discrepancy between the observed and the implied covariance matrix. The estimator is simple to implement, consistent, and asymptotically normally distributed. Least squares estimation also provides a test of model fit by comparing the observed and implied covariance matrix. The estimator and the test of model fit are evaluated in a simulation study. Although parameter recovery is good, the estimator is less efficient than the MML estimator.
authors: Martin Luther University, Halle-Wittenberg, Germany.
authors: Jochen
authors: J
authors: Ranger
authors: University of Münster, Germany.
authors: Jörg-Tobias
authors: JT
authors: Kuhn
authors: University of Münster, Germany.
authors: Carsten
authors: C
authors: Szardenings
mesh_terms: D003071:Cognition / Q000502:physiology*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D003657:Decision Making / Q000502:physiology*; D004058:Diffusion; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D011594:Psychometrics / Q000379:methods*; D011930:Reaction Time / Q000502:physiology*; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity
keywords: diffusion model; item response theory; weighted least squares