The Partial Credit Model

Masters, Geoff N

doi:10.4324/9780203861264.ch5

Cited by 41 publications

(58 citation statements)

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“…An advantage of the GPCM is that it is a generalization of other well-known item models. If all items have the same slope, the model reduces to the partial credit model, which belongs to the family of Rasch models [20]. To evaluate the effect of model choice on the item fit, we planned also to calibrate the graded response model [21], which has the same number of item parameters as the GPCM and often gives trace lines that are very similar to the GPCM trace lines [22].…”

Section: Calibration Of Irt Model and Evaluation Of Item Fitmentioning

confidence: 99%

Development of computerized adaptive testing (CAT) for the EORTC QLQ-C30 physical functioning dimension

et al. 2010

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Section: Calibration Of Irt Model and Evaluation Of Item Fitmentioning

confidence: 99%

Development of computerized adaptive testing (CAT) for the EORTC QLQ-C30 physical functioning dimension

et al. 2010

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“…The SBC was Rasch-scaled with the Quest software (Adams & Khoo, 1993) using the partial credit model for rating scales (Masters, 1997). All 24 SBC items were entered into the analysis, but only items with IMS values within the predetermined range between 0.83 and 1.20 were considered to fit the Rasch model and were retained to form a Student Behaviour Scale.…”

Section: Resultsmentioning

confidence: 99%

Teacher identification of student learned helplessness in mathematics

Yates

2009

Math Ed Res J

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“…The Nominal Categories Model (NCM) [7] and special cases of this model such as the Generalized Partial Credit Model (GPCM) [8,9], the Partial Credit Model (PCM) [10,11] and the Rating Scale Model (RSM) [12], 2. The Graded Response Model (GRM) [13,14].…”

Section: Irt Modelsmentioning

confidence: 99%

Developing tailored instruments: item banking and computerized adaptive assessment

et al. 2007

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Item banks and Computerized Adaptive Testing (CAT) have the potential to greatly improve the assessment of health outcomes. This review describes the unique features of item banks and CAT and discusses how to develop item banks. In CAT, a computer selects the items from an item bank that are most relevant for and informative about the particular respondent; thus optimizing test relevance and precision. Item response theory (IRT) provides the foundation for selecting the items that are most informative for the particular respondent and for scoring responses on a common metric. The development of an item bank is a multi-stage process that requires a clear definition of the construct to be measured, good items, a careful psychometric analysis of the items, and a clear specification of the final CAT. The psychometric analysis needs to evaluate the assumptions of the IRT model such as unidimensionality and local independence; that the items function the same way in different subgroups of the population; and that there is an adequate fit between the data and the chosen item response models. Also, interpretation guidelines need to be established to help the clinical application of the assessment. Although medical research can draw upon expertise from educational testing in the development of item banks and CAT, the medical field also encounters unique opportunities and challenges.

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The Partial Credit Model

Cited by 41 publications

References 0 publications

Development of computerized adaptive testing (CAT) for the EORTC QLQ-C30 physical functioning dimension

Development of computerized adaptive testing (CAT) for the EORTC QLQ-C30 physical functioning dimension

Teacher identification of student learned helplessness in mathematics

Developing tailored instruments: item banking and computerized adaptive assessment

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