DIFFERENT APPROACHES TO COVARIATE INCLUSION IN THE MIXTURE RASCH MODEL

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dc.contributor.advisorJiao, Hongen_US
dc.contributor.authorLi, Tongyunen_US
dc.contributor.departmentMeasurement, Statistics and Evaluationen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2015-02-07T06:31:22Z
dc.date.available2015-02-07T06:31:22Z
dc.date.issued2014en_US
dc.description.abstractThe present dissertation project investigates different approaches to adding covariates and the impact in fitting mixture item response theory (IRT) models. Mixture IRT models serve as an important methodology for tackling several important psychometric issues in test development, including detecting latent differential item functioning (DIF). A Monte Carlo simulation study is conducted in which data generated according to a two-class mixture Rasch model (MRM) with both dichotomous and continuous covariates are fitted to several MRMs with misspecified covariates to examine the effects of covariate inclusion on model parameter estimation. In addition, both complete response data and incomplete response data with different types of missingness are considered in the present study in order to simulate practical assessment settings. Parameter estimation is carried out within a Bayesian framework vis-à-vis Markov chain Monte Carlo (MCMC) algorithms. Two empirical examples using the Programme for International Student Assessment (PISA) 2009 U.S. reading assessment data are presented to demonstrate the impact of different specifications of covariate effects for an MRM in real applications.en_US
dc.identifierhttps://doi.org/10.13016/M2PD00
dc.identifier.urihttp://hdl.handle.net/1903/16256
dc.language.isoenen_US
dc.subject.pqcontrolledEducational tests & measurementsen_US
dc.subject.pqcontrolledQuantitative psychology and psychometricsen_US
dc.subject.pquncontrolledcovariate effectsen_US
dc.subject.pquncontrolledmissing dataen_US
dc.subject.pquncontrolledthe mixture Rasch modelen_US
dc.titleDIFFERENT APPROACHES TO COVARIATE INCLUSION IN THE MIXTURE RASCH MODELen_US
dc.typeDissertationen_US

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