02121nas a2200193 4500008004100000245007900041210006900120260001200189520146800201653002801669653000801697653001801705100002001723700001701743700002301760700002301783700002301806856009801829 2011 eng d00aThe Use of Decision Trees for Adaptive Item Selection and Score Estimation0 aUse of Decision Trees for Adaptive Item Selection and Score Esti c10/20113 a

Conducted post-hoc simulations comparing the relative efficiency, and precision of decision trees (using CHAID and CART) vs. IRT-based CAT.

Conclusions

Decision tree methods were more efficient than CAT

But,...

Conclusions

CAT selects items based on two criteria: Item location relative to current estimate of theta, Item discrimination

Decision Trees select items that best discriminate between groups defined by the total score.

CAT is optimal only when trait level is well estimated.
Findings suggest that combining decision tree followed by CAT item selection may be advantageous.

10aadaptive item selection10aCAT10adecision tree1 aRiley, Barth, B1 aFunk, Rodney1 aDennis, Michael, L1 aLennox, Richard, D1 aFinkelman, Matthew uhttp://mail.iacat.org/content/use-decision-trees-adaptive-item-selection-and-score-estimation