The Impact of Missing Data on Parameter Estimation: Three Examples in Computerized Adaptive Testing.
In computerized adaptive testing (CAT), examinees see items targeted to their ability level. Postoperational data have a high degree of missing information relative to designs where everyone answers all questions. Item responses are observed over a restricted range of abilities, reducing item-total...
| Publicado en: | Educational & Psychological Measurement Vol. 85; no. 3; pp. 617 - 636 |
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| Autores principales: | , |
| Formato: | Artículo |
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Sage Publications Inc.
Jun2025
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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=185038007&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 185038007 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00131644 EPM jtl: Educational & Psychological Measurement issn: 00131644 maglogo: Y pubinfo: dt: Jun2025 vid: 85 iid: 3 pid: 344 pub: Sage Publications Inc. artinfo: ui: 185038007 10.1177/00131644241306990 ppf: 617 ppct: 19 formats: tig: atl: The Impact of Missing Data on Parameter Estimation: Three Examples in Computerized Adaptive Testing. aug: au: Liu, Xiaowen Loken, Eric affil: Key Research Base of Humanities and Social Sciences of the Ministry of Education, Academy of Psychology and Behavior, Tianjin Normal University, Tianjin, China Faculty of Psychology, Tianjin Normal University, China Tianjin Key Laboratory of Student Mental Health and Intelligence Assessment, China Department of Educational Psychology, NEAG School of Education, University of Connecticut, Storrs, USA su: Parameters (Statistics) Computer adaptive testing Statistical models Scientific errors Research funding Data analysis High performance computing Probability theory Research methodology evaluation Descriptive statistics Mathematical statistics Simulation methods in education Content mining Statistics Research methodology sug: subj: Parameters (Statistics) Computer adaptive testing Statistical models Scientific errors Research funding Data analysis High performance computing Probability theory Research methodology evaluation Descriptive statistics Mathematical statistics Simulation methods in education Content mining Statistics Research methodology keyword: computerized adaptive testing item response theory missing data computerized adaptive testing item response theory missing data ab: In computerized adaptive testing (CAT), examinees see items targeted to their ability level. Postoperational data have a high degree of missing information relative to designs where everyone answers all questions. Item responses are observed over a restricted range of abilities, reducing item-total score correlations. However, if the adaptive item selection depends only on observed responses, the data are missing at random (MAR). We simulated data from three different testing designs (common items, randomly selected items, and CAT) and found that it was possible to re-estimate both person and item parameters from postoperational CAT data. In a multidimensional CAT, we show that it is necessary to include all responses from the testing phase to avoid violating missing data assumptions. We also observed that some CAT designs produced "reversals" where item discriminations became negative causing dramatic under and over-estimation of abilities. Our results apply to situations where researchers work with data drawn from adaptive testing or from instructional tools with adaptive delivery. To avoid bias, researchers must make sure they use all the data necessary to meet the MAR assumptions. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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