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Person-by-item predictors

  • Michel Meulders
  • Yiyu Xie
Part of the Statistics for Social Science and Public Policy book series (SSBS)

Abstract

In this chapter we consider the inclusion of person-by-item predictors into the model. Unlike person predictors or item predictors, person-by-item predictors vary both within and between persons. The inclusion of person-by-item predictors besides person predictors or item predictors is relevant for modeling various phenomena such as differential item functioning (DIF) and local item dependencies (LID) (see Zwinderman, 1997). To describe models with person-by-item predictors we will distinguish between static and dynamic interaction models. We concentrate here on models for DIF and LID, but the interaction concept is of course more general.

Keywords

Differential Item Functioning Item Response Item Response Theory Partial Credit Model Item Property 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Michel Meulders
  • Yiyu Xie

There are no affiliations available

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