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<p>The explanatory item response model (EIRM) is a common tool in psychometrics to model person and item characteristics as functions of covariates. Existing tutorials demonstrate how to model dichotomous or polytomous item responses. In this tutorial, we show how to fit the extended two-parameter logistic (E2PL) item response model for continuous item responses using the <Emphasis FontCategory="NonProportional">brms</Emphasis> package in R. Using two worked examples with visual analog scale data, we demonstrate data exploration, model building, and interpretation strategies. By following this tutorial, researchers will be able to fit and interpret the EIRM for continuous item response data.</p>

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Explanatory item response models for continuous data: A tutorial in R

  • 期刊论文

  • 发表日期：

    2026年4月16日

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  • Joshua B. Gilbert

摘要

The explanatory item response model (EIRM) is a common tool in psychometrics to model person and item characteristics as functions of covariates. Existing tutorials demonstrate how to model dichotomous or polytomous item responses. In this tutorial, we show how to fit the extended two-parameter logistic (E2PL) item response model for continuous item responses using the brms package in R. Using two worked examples with visual analog scale data, we demonstrate data exploration, model building, and interpretation strategies. By following this tutorial, researchers will be able to fit and interpret the EIRM for continuous item response data.