Computer Adaptive Test Stopping Rules Applied to The Flexilevel Shoulder Functioning Test

Computerized adaptive testing (CAT) is an attractive alternative to traditional paper-and-pencil testing because it can provide accurate trait estimates while administering fewer items than a linear test form. A stopping rule is an important factor in determining an assessments efficiency. This simulation compares three variable-length stopping rules-standard error (SE) of .3, minimum information (MI) of .7 and change in trait (CT) of .02 - with and without a maximum number of items (20) imposed. We use fixed-length criteria of 10 and 20 items as a comparison for two versions of a linear assessment. The MI rules resulted in longer assessments with more biased trait estimates in comparison to other rules. The CT rule resulted in more biased estimates at the higher end of the trait scale and larger standard errors. The SE rules performed well across the trait scale in terms of both measurement precision and efficiency.