How accurately ability is estimated when the test model does not fit the data is considered. To address this question, this study investigated the accuracy of the maximum likelihood estimator of ability for the one-, two- and three-parameter logistic (PL) models. The models were fitted into generated item characteristic curves derived from the…

Measurement disturbances, such as guessing, startup, and plodding, often result in an examinee's ability being either over- or under-estimated by the maximum likelihood estimation employed in latent trait psychometric models. Several authors have suggested methods to lessen the impact of unexpected responses on the ability estimation process. This…

This study compares the fit of the 3-parameter model to the Ability Removing Random Guessing (ARRG) model on data from a wide range of tests of cognitive ability in three representative samples. When the guessing parameters under the 3-parameter model are estimated individually for each item, the 3-parameter model yields the better fit to…

Latent trait theory supposes that, in testing situations, examinee performance on a test can be predicted (or explained) by defining examinee characteristics, referred to as traits, estimating scores for examinees on these traits and using the scores to predict or explain test performance (Lord and Novick, 1968). In view of the breakthroughs in…