Choosing a model, however, can present some difficulty since each model, good or otherwise, is an alternate reality. The point of making models is to bring order to our experiences and observations, and to make predictions. Models are tools for organizing reality, for ordering experiences rather than simply describing them. A description is only an account of what is. It does not motivate any investigation into the reasons why things are the way they are.
Models motivate explanations and it's clear that explanation is preferable to description.
Too often, however, the data are allowed to become the model, so that there is a different model, a new and confusing alternate reality, for every set of data collected. When the predictions provided by a model agree with what is observed, the system can be declared a model of the process under investigation. The Rasch model coordinates data with the requirements of a useful definition of measurement. The Rasch model specifies what must dominate when a person responds to a test item in order for linear measurement to be constructed. As with all real-life problems, the interaction between person and item is approximate, interconnected and occasionally misleading.