ArticleBehavioral sciences (Basel, Switzerland)2026
Quantifying Effects of Item Wording and Multiple Sources of Measurement Error Using Extended Bifactor Models.
Article in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Researchers have long known that scores from Likert-style self-report measures of psychological traits are affected by both item wording (negative and positive) and multiple sources of measurement error (specific-factor, transient, and random-response), but the magnitude of such effects is rarely separated and individually estimated within research studies. When these effects are not distinguished, as is the case when reporting conventional reliability estimates (e.g., alpha, omega, split-half, test-retest), they are confounded with trait variance and/or each other, typically resulting in overestimation of score accuracy. We demonstrate how to quantify and separate trait, wording, and multiple measurement error effects within extended bifactor models using data from a large sample of respondents (
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