Modelling non-ignorable missing data mechanisms with item response theory models

Rebecca Holman, Cornelis A.W. Glas

Research output: Contribution to journalArticleAcademic

97 Citations (Scopus)

Abstract

A model-based procedure for assessing the extent to which missing data can be ignored and handling non-ignorable missing data is presented. The procedure is based on item response theory modelling. As an example, the approach is worked out in detail in conjunction with item response data modelled using the partial credit and generalized partial credit models. Simulation studies are carried out to assess the extent to which the bias caused by ignoring the missing-data mechanism can be reduced. Finally, the feasibility of the procedure is demonstrated using data from a study to calibrate a medical disability scale.
Original languageUndefined
Pages (from-to)1-17
Number of pages17
JournalBritish journal of mathematical and statistical psychology
Volume58
Issue number1
DOIs
Publication statusPublished - 2005

Keywords

  • METIS-225592
  • IR-58611

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