Measuring Change By Means of a Hybrid Variant of the Linear Logistic Model With Relaxed Assumptions

Abstract

The linear logistic model with relaxed assumptions (LLRA) was developed for measuring changes in quali tative data. It assumes item-specific person parameters and thus does not require homogeneous items to be presented to the persons at two points in time. The hybrid variant of this model maintains the multidimen sionality of the person parameters, but it allows for different sets of items each of which is presented only once. In the model, a Rasch homogeneous item at t ₂ with possibly differing difficulty corresponds to each item at t ₁. A short description of both models is fol lowed by a first application of the hybrid LLRA to em pirical data from a study on text comprehension. This example not only serves to demonstrate possible re sults when applying the LLRA, but is also used to out line the principle of hypothesis testing and model con trols. Index terms: dichotomous data, linear logistic model, measuring change, Rasch model, text compre hension.