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Same Test, Better Scores: Boosting the Reliability of Short Online Intelligence Recruitment Tests with Nested Logit Item Response Theory Models
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Storme, Martin; Myszkowski, Nils; Baron, Simon; Bernard, David – Journal of Intelligence, 2019
Assessing job applicants' general mental ability online poses psychometric challenges due to the necessity of having brief but accurate tests. Recent research (Myszkowski & Storme, 2018) suggests that recovering distractor information through Nested Logit Models (NLM; Suh & Bolt, 2010) increases the reliability of ability estimates in…
Descriptors: Intelligence Tests, Item Response Theory, Comparative Analysis, Test Reliability