Explanatory item response models : a generalized linear and nonlinear approach

Bibliographic Information

Explanatory item response models : a generalized linear and nonlinear approach

Paul de Boeck, Mark Wilson, editors

(Statistics for social science and public policy)

Springer, c2004

Available at  / 15 libraries

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Includes bibliographical references and index

Description and Table of Contents

Description

This edited volume gives a new and integrated introduction to item response models (predominantly used in measurement applications in psychology, education, and other social science areas) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. It also includes a chapter on the statistical background and one on useful software.

Table of Contents

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.- Afterword.

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