Plausible Values: Principles of Item Response Theory and Multiple Imputations

Abstract

This chapter introduces the principles of item response theory (IRT) and the latent regression model, also called population or conditioning model, which is central for generating plausible values (multiple imputations) in PIAAC. Moreover, it is illustrated how plausible values can reduce bias in secondary analyses compared to the use of customary point estimates of latent variables by taking explanatory variables into account. An overview of standard techniques for utilizing plausible values (PVs) in the analyses of large-scale assessment data will be provided, and it will be discussed how to calculate the different variance components for statistics based on PVs, which play an important role in the interpretation of subgroup and country differences.

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