Enhancing Computerized Adaptive Testing with Batteries of Unidimensional Tests.

The article presents a new computerized adaptive testing (CAT) procedure for use with batteries of unidimensional tests. At each step of testing, the estimate of a certain ability is updated on the basis of the response to the latest administered item and the current estimates of all other abilities measured by the battery. The information deriving from these abilities is incorporated into an empirical prior that is updated each time that new estimates of the abilities are computed. In two simulation studies, the performance of the proposed procedure is compared with that of a standard procedure for CAT with batteries of unidimensional tests. The proposed procedure yields more accurate ability estimates in fixed-length CATs, and a reduction of test length in variable-length CATs. These gains in accuracy and efficiency increase with the correlation between the abilities measured by the batteries.

Assessing the impact of replication on implicit association test effect by means of the extended logistic model for the assessment of change.

The present study consists of a longitudinal investigation in which implicit association measures were collected by means of the implicit association test (IAT), with the purpose of assessing the impact of replication on the test effect with the same participants. The extended logistic model for the assessment of change (ELMAC), a procedure that belongs to Rasch modeling, was applied. By means of the ELMAC application, the existence of latent traits characteristic of the impact on the IAT effect (due to replication through time) is shown; more precisely, the model time parameters show the decrement of the IAT effect through time, due to the decrease of the implicit preference in both conditions, compatible and incompatible, associated with sweet foods and salty foods. The results confirm that in the long run, the incompatible condition latency may approach the compatible condition latency, causing a significant attenuation of the IAT effect.

Assessing change with the extended logistic model.

The purpose of this article is to define a method for the assessment of change. A reinterpretation of the extended logistic model is proposed. The extended logistic model for the assessment of change (ELMAC) allows the definition of a time parameter which is supposed to identify whether change occurs during a period of time, given a specific event or phenomenon. The assessment of a trend of change through time, on the basis of the time parameter which is estimated at different successive occasions during a period of time, is also considered. In addition, a dispersion parameter is calculated which identifies whether change is consistent at each time point. The issue of independence is taken into account both in relation to the time parameter and the dispersion parameter. An application of the ELMAC in a learning process is presented. The interpretation of the model parameters and the model fit statistics is consistent with expectations.