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Discriminating Between Attribute, Item-Position, and Wording Effects by the Congeneric and Tau-Equivalent Confirmatory Factor Analysis Models

Karl Schweizer et al.

Educational and Psychological Measurement2026https://doi.org/10.1177/00131644261419028article
ABDC A
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0.50

Abstract

The capability of confirmatory factor analysis to discriminate common systematic variation of attribute, item-position, and wording effects was investigated using the congeneric and tau-equivalent models. The simulated data generated according to four approaches included gradually increased amounts of item-position or wording effect variation while the amount of attribute variation was kept constant. The congeneric model always signified good model fit independently of the type and amount of additional common systematic variation, that is, there was no discrimination. In applications of the tau-equivalent model, the increase of the item-position or wording effect variation led to the change from indicating good fit to bad model fit, that is, there was negative discrimination. In contrast, the additionally considered two-factor tau model discriminated positively. As a consequence of these results, we recommend the pre-screening of data for method effects.

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https://doi.org/https://doi.org/10.1177/00131644261419028

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@article{karl2026,
  title        = {{Discriminating Between Attribute, Item-Position, and Wording Effects by the Congeneric and Tau-Equivalent Confirmatory Factor Analysis Models}},
  author       = {Karl Schweizer et al.},
  journal      = {Educational and Psychological Measurement},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/00131644261419028},
}

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Discriminating Between Attribute, Item-Position, and Wording Effects by the Congeneric and Tau-Equivalent Confirmatory Factor Analysis Models

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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