title: A Dual-Purpose Rasch Model with Joint Maximum Likelihood Estimation.
abstract: In practice, there is a growing need of reporting both overall score for the ranking/decision-making purpose and subscores for the diagnostic purpose. The Rasch model with subdimensions (RMS) was employed in this study to address this problem. A joint maximum likelihood estimation (JMLE) procedure was proposed to obtain computationally efficient estimation for this model. A simulation study was conducted to investigate the properties of this model with the JMLE procedure in conditions with varying sample size, test lengths and subdimension loading structure. Results indicated that in general, parameters were estimated well using the JMLE procedure. The item parameters and overall ability parameters in RMS were in accordance with parameters obtained from the Rasch model.
authors.forename: Xiao
authors.initials: X
authors.lastname: Luo
authors.forename: John T
authors.initials: JT
authors.lastname: Willse
mesh_terms: D003657:Decision Making; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D018401:Sample Size