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On the Use of IRT Models With Judgmental Standard Setting Procedures
Author(s) -
Kane Michael T.
Publication year - 1987
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.1987.tb00284.x
Subject(s) - generalizability theory , item response theory , test (biology) , statistic , psychology , computer science , test theory , classical test theory , econometrics , polytomous rasch model , statistics , psychometrics , mathematics , clinical psychology , paleontology , biology
In judgmental standard setting procedures (e.g., the Angoff procedure), expert raters establish minimum pass levels (MPLs) for test items, and these MPLs are then combined to generate a passing score for the test. As suggested by Van der Linden (1982), item response theory (IRT) models may be useful in analyzing the results of judgmental standard setting studies. This paper examines three issues relevant to the use of lRT models in analyzing the results of such studies. First, a statistic for examining the fit of MPLs, based on judges' ratings, to an IRT model is suggested. Second, three methods for setting the passing score on a test based on item MPLs are analyzed; these analyses, based on theoretical models rather than empirical comparisons among the three methods, suggest that the traditional approach (i.e., setting the passing score on the test equal to the sum of the item MPLs) does not provide the best results. Third, a simple procedure, based on generalizability theory, for examining the sources of error in estimates of the passing score is discussed.