Open AccessCLASSICAL TEST THEORY AS A FIRST‐ORDER ITEM RESPONSE THEORY: APPLICATION TO TRUE‐SCORE PREDICTION FROM A POSSIBLY NONPARALLEL TEST
Author(s) -
Holland Paul W.,
Hoskens Machteld
Publication year - 2002
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/j.2333-8504.2002.tb01887.x
Subject(s) - item response theory , classical test theory , rasch model , test theory , test (biology) , score test , test score , econometrics , population , set (abstract data type) , statistics , equating , mathematics , psychometrics , computer science , statistical hypothesis testing , standardized test , paleontology , demography , sociology , biology , programming language
We give an account of classical test theory (CTT) in terms of the more fundamental ideas of item response theory (IRT). This approach views CTT as a very general version of IRT, and the commonly used IRT models as detailed elaborations of CTT for special purposes. We then use this approach to CTT to derive some general results regarding the prediction of the true score of a test from an observed score on that test as well from an observed score on a different test. This leads us to a new view of linking tests that were not developed to be linked to each other. In addition we propose true‐score prediction analogues of the Dorans and Holland measures of the population sensitivity of test linking functions. We illustrate the accuracy of the first‐order theory using simulated data from the Rasch model and illustrate the effect of population differences using a set of real data.