Introduction to Nonparametric Item Response Theory addresses an important and complex topic in test development in a manner that is precise and accurate, yet accessible to students and practitioners with a modest background in classical test theory. It also provides an excellent introduction to nonparametric IRT models for the more mathematically sophisticated student or researcher who will welcome the extensive additonal reading lists that are found at the conclusion of each chapter.

Categorical data are quantified as either nominal variables--distinguishing different groups, for example, based on socio-economic status, education, and political persuasion--or ordinal variables--distinguishing levels of interest, such as the preferred politician or the preferred type of punishment for committing burglary. This new book is a collection of up-to-date studies on modern categorical data analysis methods, emphasizing their application to relevant and interesting data sets.
This volume concentrates on latent class analysis and item response theory. These methods use latent...

Categorical data are quantified as either nominal variables--distinguishing different groups, for example, based on socio-economic status, education, and political persuasion--or ordinal variables--distinguishing levels of interest, such as the preferred politician or the preferred type of punishment for committing burglary. This new book is a collection of up-to-date studies on modern categorical data analysis methods, emphasizing their application to relevant and interesting data sets. This volume concentrates on latent class analysis and item response theory. These methods use latent...