Search alternatives:
significantly reduce » significantly reduced (Expand Search), significantly greater (Expand Search), significantly enhance (Expand Search)
reduce decrease » reduce disease (Expand Search), reduce depressive (Expand Search), induces decreased (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
gap decrease » a decrease (Expand Search), gain decreased (Expand Search), mean decrease (Expand Search)
significantly reduce » significantly reduced (Expand Search), significantly greater (Expand Search), significantly enhance (Expand Search)
reduce decrease » reduce disease (Expand Search), reduce depressive (Expand Search), induces decreased (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
gap decrease » a decrease (Expand Search), gain decreased (Expand Search), mean decrease (Expand Search)
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EF-24 treatment significantly reduces cell viability in leukemia cell lines.
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Effect of the smoking factor on lung function parameters (FVC, FEV1, PEF, FEF 25_75).
Published 2025Subjects: -
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Preference for the EIA – conjoint results.
Published 2025“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”
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Marginal means – Pooled across scenarios.
Published 2025“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”
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Sample attribute table.
Published 2025“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”
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Subgroup analysis – Political affiliation.
Published 2025“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? A randomized conjoint experiment and a follow-up choice experiment revealed that support for the EIAs decreased sharply as their accuracy gap grew, although impact parity was prioritized more when ETAs produced large outcome discrepancies. …”