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dc.contributor.advisorOsterlind, Steven J.eng
dc.contributor.authorSheng, Zhaohuieng
dc.date.issued2007eng
dc.date.submitted2007 Summereng
dc.descriptionThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.eng
dc.descriptionTitle from title screen of research.pdf file (viewed on December 28, 2007)eng
dc.descriptionThesis (Ph. D.) University of Missouri-Columbia 2007.eng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The study investigates population invariance of equating functions in situations where equating samples are considerably unequal in size. Using an equivalent groups equating design, the study compares equating functions developed from the linear equating procedure, the unsmoothed equipercentile equating procedure, and the three-parameter IRT true-score equating procedure on examinee samples that were formed based on gender and ethnicity as well as on the total examinee sample. Multiple evaluative measures were used to evaluate equating differences. Findings indicate that equating invariance was reasonably achieved across the gender groups, that lack of equating invariance was found for the ethnic groups, and that the IRT true-score equating did not perform better in terms of robustness to form or group differences. The study findings suggest that sample sizes do influence equating invariance. With samples unequal in size, equating functions developed from the total examinee sample tend to be influences by the dominating examinee group, whereas equating functions obtained from small examinee samples are subject to larger sampling error. The study recommends linear equating for small equating samples based on examination of equating precision. Investigation of invariance of score classifications supports the use of linear equating with small equating samples becuase of better classification consistency. Higher consistency was found at passing scores that are farther away from the mean, suggesting that the location of cutoff scores impacts classification consistency. When equating samples are small, using cutoff scores may be a practical alternative to better equating invariance.eng
dc.description.bibrefIncludes bibliographical referenceseng
dc.identifier.merlinb61718476eng
dc.identifier.oclc185057407eng
dc.identifier.urihttps://doi.org/10.32469/10355/5929eng
dc.identifier.urihttps://hdl.handle.net/10355/5929
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsAccess is limited to the campus of the University of Missouri--Columbia.eng
dc.subject.lcshExaminations -- Scoringeng
dc.subject.lcshEducational tests and measurementseng
dc.subject.lcshStudents -- Rating ofeng
dc.subject.lcshFunctional equationseng
dc.subject.lcshPopulationeng
dc.titleUsing population invariance as a criterion to evaluate equating relationship for college basic academic subject examinationeng
dc.typeThesiseng
thesis.degree.disciplineEducational, school and counseling psychology (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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