Search alternatives:
greatest decrease » treatment decreased (Expand Search), greater increase (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
gap decrease » gain decreased (Expand Search), mean decrease (Expand Search), step decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
greatest decrease » treatment decreased (Expand Search), greater increase (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
gap decrease » gain decreased (Expand Search), mean decrease (Expand Search), step decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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201
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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202
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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203
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. …”
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204
Sample scenario description.
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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205
AMCEs – 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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206
Methodological flowchart.
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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207
Preference for the EIA vs. ETA 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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Decreased clonogenic capacity of U87MG and U251MG glioma cells dependent on SHG-44 concentration.
Published 2025“…<p><b>(A)</b> A significant decrease in the proliferative clonal capacity of U87MG colonies was observed with 70ΜM and 100ΜM SHG-44 treatment. …”
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219
HFD decreases ITM and alters metabolic homeostasis.
Published 2025“…Two-way ANOVA, n.s., not significant, ** p < 0.01). <b>(F)</b> Long-term memory (LTM) was significantly decreased in the HFD group. …”
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220