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Four meaningful item clusters were identified, each reflecting more cognitively advanced empathic attitudes.
The booklet design consisted of several complex Youden square designs (Frey et al. 2009), including 42 booklets each with three item clusters, 10 items per cluster.
However, since it would not be sensible to administer a test of more than 6 hours to an individual pupil, 13 largely comparable item clusters, with a duration of 2 hours each, were derived from the core test.
The 184 main survey items were allocated to 13 half-hour (30-minute) mutually exclusive item clusters that included seven science clusters, four mathematics clusters, and two reading clusters.
Each of the three primary scales is comprised of several item clusters.
One of these two item clusters comprised all DED items, while the other comprised all OBN and VRS items.
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Two levels of testlet contamination were manipulated by either generating item clustering effect in the second testlet, or not generating item clustering effect in the second testlet.
These methods, however, only focused on the item clustering effect in DIF analysis.
In order to account for the item clustering effect on DIF analysis, several DIF methods have been developed.
In addition, the performance of non-parametric DIF methods can also be adversely affected by the item clustering effect.
Another DIF method was to employ the bifactor model to account for the item clustering effect (Cai et al. 2011; Jeon et al. 2013).
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