Cognitive Diagnosis Models (CDMs) are a special family of discrete latent variable models that are widely used in educational and psychological measurement. A key component of CDMs is the Q-matrix characterizing the dependence structure between the items and the latent attributes. Additionally, researchers also assume in many applications certain…

Topic models are mathematical and statistical models used to analyze textual data. The objective of topic models is to gain information about the latent semantic space of a set of related textual data. The semantic space of a set of textual data contains the relationship between documents and words and how they are used. Topic models are becoming…

Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical…

Maximum likelihood procedures are presented for a general model to unify the various models and techniques that have been proposed for item analysis. Unconditional maximum likelihood estimation, proposed by Wright and Haberman, and conditional maximum likelihood estimation, proposed by Rasch and Andersen, are shown as important special cases. (JAZ)

Combining Rasch and latent class models is presented as a way to overcome deficiencies and retain the positive features of both. An estimation algorithm is outlined, providing conditional maximum likelihood estimates of item parameters for each class. The model is illustrated with simulated data and real data (n=869 adults). (SLD)

On well-constructed multiple-choice tests, the most serious threat to measurement is not variation in item discrimination, but the guessing behavior that may be adopted by some students. Ways of ameliorating the effects of guessing are discussed, especially for problems in latent trait models. A new item response model, including an item parameter…

This paper discusses the use of latent class structure as a modelling framework for tests in which much of the data conforms to a relatively small number of systematic patterns. Application of this framework to the analysis of tests has been limited because available parameter estimation algorithms can only handle a relatively small number of…

This report summarizes the results of research designed to study the psychometric and technological feasibility of adaptive testing to assess spatial ability. Data was collected from high school students on two types of spatial items: three-dimensional cubes and hidden figure items. The analysis of the three-dimensional cubes focused on the fit of…

This paper reports on a project which has developed the general latent class model as a framework for representation of item responses. This framework can be used to represent data in applications such as mastery tests and other kinds of achievement tests, where there is reason to believe that current foundations are deficient. Methods of…