A comparison of Andrich's rating scale model and Rost's succesive intervals model

dc.contributor.advisorDood, Barbara Glenzingen
dc.creatorLustina, Michael Johnen
dc.date.accessioned2008-08-28T21:57:33Zen
dc.date.available2008-08-28T21:57:33Zen
dc.date.issued2004en
dc.descriptiontexten
dc.description.abstractThis study compared and contrasted two IRT models for measuring attitudes: Andrich’s rating scale model (ARSM) and Rost’s successive intervals model (SIM). While these IRT models require that the attitude scale be unidimensional, they make different assumptions in the development of their item parameters. The ARSM and SIM were compared in the context of a computer adaptive test (CAT). Two data sets were used. The Audit of Administrator Communication (ADCOM) data set is archival and allowed for comparison of the models in an actual testing environment. A second data set was simulated using the linear factor analytic approach. The models were compared using Pearson product-moment correlations, standard errors and number of items administered during a CAT. In addition, RMSE and bias estimates were calculated. Results indicated that each model has advantages within a CAT context. The ARSM provided a better estimate of theta and the SIM required fewer items to estimate theta. Suggestions are provided as to the choice of model to use in different research settings.
dc.description.departmentEducational Psychologyen
dc.format.mediumelectronicen
dc.identifierb59327807en
dc.identifier.oclc57894616en
dc.identifier.proqst3150687en
dc.identifier.urihttp://hdl.handle.net/2152/1363en
dc.language.isoengen
dc.rightsCopyright is held by the author. Presentation of this material on the Libraries' web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works.en
dc.subject.lcshItem response theoryen
dc.subject.lcshSocial sciences--Mathematical modelsen
dc.titleA comparison of Andrich's rating scale model and Rost's succesive intervals modelen
dc.type.genreThesisen

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