يعرض 621 - 640 نتائج من 21,342 نتيجة بحث عن '(( significant decrease decrease ) OR ( ((significant co) OR (significant gap)) decrease ))*', وقت الاستعلام: 0.83s تنقيح النتائج
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    Analysis of the Nugent score before (T=0) and after (T=1) the use of the vaginal gel. Number of participants and respective percentages of Nugent scores before and after the intervention. A statistically significant decrease in Nugent scores was observed after the intervention (p value =0.0047). حسب Adriana Bittencourt Campaner (21175462)

    منشور في 2025
    "…Number of participants and respective percentages of Nugent scores before and after the intervention. A statistically significant decrease in Nugent scores was observed after the intervention (p value =0.0047).…"
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    Preference for the EIA – conjoint results. حسب Mehdi Mourali (10170245)

    منشور في 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. …"
  15. 635

    Marginal means – Pooled across scenarios. حسب Mehdi Mourali (10170245)

    منشور في 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. …"
  16. 636

    Sample attribute table. حسب Mehdi Mourali (10170245)

    منشور في 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. …"
  17. 637

    Subgroup analysis – Political affiliation. حسب Mehdi Mourali (10170245)

    منشور في 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 scenario description. حسب Mehdi Mourali (10170245)

    منشور في 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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    AMCEs – Pooled across scenarios. حسب Mehdi Mourali (10170245)

    منشور في 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. …"
  20. 640

    Methodological flowchart. حسب Mehdi Mourali (10170245)

    منشور في 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. …"