The presentation provides new results on a form of adaptive testing that is used frequently in intelligence testing. In these tests, items are presented in order of increasing difficulty, and the presentation of items is adaptive in the sense that each subtest session is discontinued once a test taker produces a certain number of incorrect responses in sequence. The subsequent (not observed) responses are commonly scored as wrong for that subtest, even though the test taker has not seen these. Discontinuation rules allow a certain form of adaptiveness both in paper-based and computerbased testing, and help reducing testing time.

Two lines of research that are relevant are studies that directly assess the impact of discontinuation rules, and studies that more broadly look at the impact of scoring rules on test results with a large number of not administered or not reached items. He & Wolf (2012) compared different ability estimation methods for this type of discontinuation rule adaptation of test length in a simulation study. However, to our knowledge there has been no rigorous analytical study of the underlying distributional changes of the response variables under discontinuation rules. It is important to point out that the results obtained by He & Wolf (2012) agree with results presented by, for example, DeAyala, Plake & Impara (2001) as well as Rose, von Davier & Xu (2010) and Rose, von Davier & Nagengast (2016) in that ability estimates are biased most when scoring the not observed responses as wrong. Discontinuation rules combined with scoring the non-administered items as wrong is used operationally in several major intelligence tests, so more research is needed in order to improve this particular type of adaptiveness in the testing practice.

The presentation extends existing research on adaptiveness by discontinue-rules in intelligence tests in multiple ways: First, a rigorous analytical study of the distributional properties of discontinue-rule scored items is presented. Second, an extended simulation is presented that includes additional alternative scoring rules as well as bias-corrected ability estimators that may be suitable to improve results for discontinue-rule scored intelligence tests.

References: DeAyala, R. J., Plake, B. S., & Impara, J. C. (2001). The impact of omitted responses on the accuracy of ability estimation in item response theory. Journal of Educational Measurement, 38, 213-234.

He, W. & Wolfe, E. W. (2012). Treatment of Not-Administered Items on Individually Administered Intelligence Tests. Educational and Psychological Measurement, Vol 72, Issue 5, pp. 808 – 826. DOI: 10.1177/0013164412441937

Rose, N., von Davier, M., & Xu, X. (2010). Modeling non-ignorable missing data with item response theory (IRT; ETS RR-10-11). Princeton, NJ: Educational Testing Service.

Rose, N., von Davier, M., & Nagengast, B. (2016) Modeling omitted and not-reached items in irt models. Psychometrika. doi:10.1007/s11336-016-9544-7

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