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Bayesian modification indices for IRT models

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  • Jean‐Paul Fox
  • Cees A. W. Glas

Abstract

Bayesian modification indices are presented that provide information for the process of model evaluation and model modification. These indices can be used to investigate the improvement in a model if fixed parameters are re‐specified as free parameters. The indices can be seen as a Bayesian analogue to the modification indices commonly used in a frequentist framework. The aim is to provide diagnostic information for multi‐parameter models where the number of possible model violations and the related number of alternative models is too large to render estimation of each alternative practical. As an example, the method is applied to an item response theory (IRT) model, that is, to the two‐parameter model. The method is used to investigate differential item functioning and violations of the assumption of local independence.

Suggested Citation

  • Jean‐Paul Fox & Cees A. W. Glas, 2005. "Bayesian modification indices for IRT models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(1), pages 95-106, February.
    • Handle: RePEc:bla:stanee:v:59:y:2005:i:1:p:95-106
    DOI: 10.1111/j.1467-9574.2005.00282.x
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    Cited by:

    1. Guastadisegni, Lucia & Cagnone, Silvia & Moustaki, Irini & Vasdekis, Vassilis, 2022. "Use of the Lagrange multiplier test for assessing measurement invariance under model misspecification," LSE Research Online Documents on Economics 110358, London School of Economics and Political Science, LSE Library.
    2. Padilla, Juan L. & Azevedo, Caio L.N. & Lachos, Victor H., 2018. "Multidimensional multiple group IRT models with skew normal latent trait distributions," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 250-268.
    3. Azevedo, Caio L.N. & Andrade, Dalton F. & Fox, Jean-Paul, 2012. "A Bayesian generalized multiple group IRT model with model-fit assessment tools," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4399-4412.

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