ArticleEducational and psychological measurement2020
Identifying Effortful Individuals With Mixture Modeling Response Accuracy and Response Time Simultaneously to Improve Item Parameter Estimation.
Article in Educational and psychological measurement, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Dependent latent class partial credit models for careless and insufficient effort responding in online survey data.Behavior research methods · 2026Article
- A Two-Step Method Based on lz* for Identifying Effortful Respondents.Journal of Intelligence · 2026Article
- A modified hidden Markov model for detecting insufficient effort responses in questionnaires.Behavior research methods · 2025Article
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3 authors.
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Abstract
The responses of non-effortful test-takers may have serious consequences as non-effortful responses can impair model calibration and latent trait inferences. This article introduces a mixture model, using both response accuracy and response time information, to help differentiating non-effortful and effortful individuals, and to improve item parameter estimation based on the effortful group. Two mixture approaches are compared with the traditional response time mixture model (TMM) method and the normative threshold 10 (NT10) method with response behavior effort criteria in four simulation scenarios with regard to item parameter recovery and classification accuracy. The results demonstrate that the mixture methods and the TMM method can reduce the bias of item parameter estimates caused by non-effortful individuals, with the mixture methods showing more advantages when the non-effort severity is high or the response times are not lognormally distributed. An illustrative example is also provided.
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