Abstract:
:Cluster analysis can be a useful statistical technique for setting minimum passing scores on high-stakes examinations by grouping examinees into homogenous clusters based on their responses to test items. It has been most useful for supplementing data or validating minimum passing scores determined from expert judgment approaches, such as the Ebel and Nedelsky methods. However, there is no evidence supporting how well cluster analysis converges with the modified Angoff method, which is frequently used in medical credentialing. Therefore, the purpose of this study is to investigate the efficacy of cluster analysis for validating Angoff-derived minimum passing scores. Data are from 652 examinees who took a national credentialing examination based on a content-by-process test blueprint. Results indicate a high degree of consistency in minimum passing score estimates derived from the modified Angoff and cluster analysis methods. However, the stability of the estimates from cluster analysis across different samples was modest.
journal_name
Eval Health Profjournal_title
Evaluation & the health professionsauthors
Hess B,Subhiyah RG,Giordano Cdoi
10.1177/0163278707307904subject
Has Abstractpub_date
2007-12-01 00:00:00pages
362-75issue
4eissn
0163-2787issn
1552-3918pii
30/4/362journal_volume
30pub_type
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