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A Method for Detecting Regression of Hard and Easy Item Angoff Ratings
Author(s) -
Wyse Adam E.,
Babcock Ben
Publication year - 2019
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/jedm.12199
Subject(s) - standard deviation , statistics , scale (ratio) , standard error , psychology , mathematics , computer science , econometrics , quantum mechanics , physics
One common phenomenon in Angoff standard setting is that panelists regress their ratings in toward the middle of the probability scale. This study describes two indices based on taking ratios of standard deviations that can be utilized with a scatterplot of item ratings versus expected probabilities of success to identify whether ratings are regressed in toward the middle of the probability scale. Results from a simulation study show that the standard deviation ratio indices can successfully detect ratings for hard and easy items that are regressed in toward the middle of the probability scale in Angoff standard‐setting data, where previously proposed indices often do not work as well to detect these effects. Results from a real data set show that, while virtually all raters improve from Round 1 to Round 2 as measured by previously developed indices, the standard deviation ratios in conjunction with a scatterplot of item ratings versus expected probabilities of success can identify individuals who may still be regressing their ratings in toward the middle of the probability scale even after receiving feedback. The authors suggest using the scatterplot along with the standard deviation ratio indices and other statistics for measuring the quality of Angoff standard‐setting data.