The book starts with a four-chapter section containing an introduction to the framework. The remaining chapters describe models for ordered-category data, multilevel models, models for differential item functioning, multidimensional models, models for local item dependency, and mixture models. It also includes a chapter on the statistical background and one on useful software. In order to make the task easier for the reader, a unified approach to notation and model description is followed throughout the chapters, and a single data set is used in most examples to make it easier to see how the many models are related. For all major examples, computer commands from the SAS package are provided that can be used to estimate the results for each model. In addition, sample commands are provided for other major computer packages.

Title:Explanatory Item Response Models  A Generalized Linear and Nonlinear Approach
Author:Paul De Boeck;Mark Wilson
Hardcover: 393pages
Publisher: Springer
Language: English
ISBN: 9781475739909

1 A framework for item response models.
2 Descriptive and explanatory item response models.
3 Models for polytomous data.-
4 An Introduction to (Generalized (Non)Linear Mixed Models.
5 Person regression models.-
6 Models with item and item group predictors.
7 Person-by-item predictors.
8 Multiple person dimensions and latent item predictors.
9 Latent item predictors with fixed effects.
10 Models for residual dependencies.
11 Mixture Models.
12 Estimation and software.