In psychological research, the assessment of most constructs is affected by measurement error. Measurement error results in biased estimates of population parameters and their standard errors. In the past few decades, in the area of large-scale assessment studies, the plausible values technique has been established as a procedure for correcting relationships between latent variables and covariates. The present article introduces this complex statistical technique using a simple example from classic test theory. It shows that alternative procedures for estimating person parameters result in biased estimates of relationships at the population level. A simulation study was conducted to demonstrate that these findings also hold for an item response model in the case of dichotomous indicators. The results highlight that plausible values should not be used for estimating individual person parameters and are not appropriate for individual psychological assessment. Finally, we discuss methodological challenges in the application of the plausible value technique and the potential of this technique for psychological research.
Translated title of the contributionAn introduction to the Plausible Value Technique for psychological research
Original languageGerman
Issue number3
Pages (from-to)193-205
Number of pages13
Publication statusPublished - 2017
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    Research areas

  • plausible values, large-scale assessment, latent variables, reliability, missing data

ID: 665967