Many educational tests use testlets as a way of providing context. When testlet effect and item idiosyncratic features of individual items are both considered to be the reasons of DIF in many educational tests using testlets, it is interesting to investigate the phenomena of DIF amplification and cancellation resulting from the interactive effects of these two factors. This research presented a study based on a multiple-group testlet item response theory model to examine in detail different situations of DIF amplification and cancellation at the item and testlet level using testlet characteristic curve procedures with signed/ unsigned area indices and logistic regression procedure. The testlet DIF model was estimated using a hierarchical Bayesian framework with the Markov Chain Monte Carlo method. The simulation study investigated all of the possible conditions of DIF amplification and cancellation. Real data analysis indicated the existence of testlet effect and its magnitudes of difference on the means and/or variance of testlet distribution between manifest groups such as gender or ethnicity.
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Many educational tests use testlets as a way of providing context. When testlet effect and item idiosyncratic features of individual items are both considered to be the reasons of DIF in many educational tests using testlets, it is interesting to investigate the phenomena of DIF amplification and cancellation resulting from the interactive effects of these two factors. This research presented a study based on a multiple-group testlet item response theory model to examine in detail different situations of DIF amplification and cancellation at the item and testlet level using testlet characteristic curve procedures with signed/ unsigned area indices and logistic regression procedure. The testlet DIF model was estimated using a hierarchical Bayesian framework with the Markov Chain Monte Carlo method. The simulation study investigated all of the possible conditions of DIF amplification and cancellation. Real data analysis indicated the existence of testlet effect and its magnitudes of difference on the means and/or variance of testlet distribution between manifest groups such as gender or ethnicity.
Dr. Han Bao is an Assistant Professor at the Shanghai Normal University, College Of Education. She graduated from the University of Maryland, College Park, majoring in Measurement, Statistics and Evaluation. Her research interests lie in Educatinal Statisics & Measurement theories.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bao HanDr. Han Bao is an Assistant Professor at the Shanghai Normal nUniversity, College Of Education. She graduated from the nUniversity of Maryland, College Park, majoring in nMeasurement, Statistics and Evaluation. Her research ni. N° de réf. du vendeur 4963340
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Taschenbuch. Etat : Neu. DIFFERENTIAL ITEM FUNCTION AMPLIFICATION AND CANCELLATION | IN APPLICATION OF ITEM RESPONSE TESTLET MODEL | Han Bao | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639165494 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 101553656
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Many educational tests use testlets as a way of providing context. When testlet effect and item idiosyncratic features of individual items are both considered to be the reasons of DIF in many educational tests using testlets, it is interesting to investigate the phenomena of DIF amplification and cancellation resulting from the interactive effects of these two factors. This research presented a study based on a multiple-group testlet item response theory model to examine in detail different situations of DIF amplification and cancellation at the item and testlet level using testlet characteristic curve procedures with signed/ unsigned area indices and logistic regression procedure. The testlet DIF model was estimated using a hierarchical Bayesian framework with the Markov Chain Monte Carlo method. The simulation study investigated all of the possible conditions of DIF amplification and cancellation. Real data analysis indicated the existence of testlet effect and its magnitudes of difference on the means and/or variance of testlet distribution between manifest groups such as gender or ethnicity. N° de réf. du vendeur 9783639165494
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