Item response theory.
Part of a special section on advanced quantitative methods in counseling psychology. The writers analyze item response theory (IRT), which seeks to model a way in which latent psychological constructs manifest themselves in terms of observable item responses and is useful in the development, evalua...
| Publicado en: | Counseling Psychologist Vol. 27; no. 3; pp. 353 - 384 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Sage Publications Inc.
May 1999
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=507629735&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 507629735 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00110000 CPG jtl: Counseling Psychologist issn: 00110000 maglogo: N pubinfo: dt: May 1999 vid: 27 iid: 3 pid: 344 pub: Sage Publications Inc. artinfo: ui: 507629735 10.1177/0011000099273004 ppf: 353 ppct: 31 formats: tig: atl: Item response theory. aug: au: Harvey, Robert J. Hammer, Allen L. su: Psychological techniques Psychometrics Counseling psychology Item response theory sug: subj: Psychological techniques Psychometrics Counseling psychology Item response theory ab: Part of a special section on advanced quantitative methods in counseling psychology. The writers analyze item response theory (IRT), which seeks to model a way in which latent psychological constructs manifest themselves in terms of observable item responses and is useful in the development, evaluation, and scoring of tests. After an overview of the most popular IRT models is presented and they are contrasted with techniques used in classical test theory, the application of IRT using data from the recently revised Myers-Briggs Type Indicator is illustrated. These results highlight a number of IRT's advantages, which include detailed descriptions of the performance of individual items; indices of item- and scale-level precision that are free to vary across the full-range of possible scores; assessments of item- and test-level bias with respect to demographic subgroups; measures of response-profile quality; and computer-adaptive testing, which can greatly reduce testing time. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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