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

“…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. …”

Sample scenario description. by Mehdi Mourali (10170245)

“…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. …”

AMCEs – Pooled across scenarios. by Mehdi Mourali (10170245)

“…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. …”

Methodological flowchart. by Mehdi Mourali (10170245)

“…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. …”

Preference for the EIA vs. ETA across scenarios. by Mehdi Mourali (10170245)

“…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. …”

SD under different weights. by Jianrong Cai (14245136)

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Model framework. by Jianrong Cai (14245136)

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Vehicle travel time. by Jianrong Cai (14245136)

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SD under different penetration rates. by Jianrong Cai (14245136)

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Notation description. by Jianrong Cai (14245136)

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Five-stage speed adjustment. by Jianrong Cai (14245136)

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Mean TTC under different weights. by Jianrong Cai (14245136)

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SD and mean TTC under different weights. by Jianrong Cai (14245136)

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Parameter values. by Jianrong Cai (14245136)

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Trends of incident opioid users, L-TOT users, and L-TOT discontinuers between 2009 and 2013. by Qian Cai (112039)

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The yearly numerator, denominator and rate of incident opioid users, L-TOT users and L-TOT discontinuers from 2009 to 2019. by Qian Cai (112039)

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Incidence rate ratios of negative binominal regression models for yearly rates of incident opioid users, L-TOT users and L-TOT discontinuers during 2009–2013 and 2015–2019. by Qian Cai (112039)

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Demographic, comorbidity, concurrent drug, and opioid characteristics, among L-TOT users and L-TOT discontinuers between 2009–2019. by Qian Cai (112039)

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The heatmap of two types high alcohol use-related Stroke showing ASMR (A), ASDR (B), Age-Standardized Rate of YLDs (C), and Age-Standardized Rate of YLLs (D) across 21 GBD regions... by Nannan Qian (10650782)

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Health inequality regression curves and concentration curves for the DALYs of two types of high alcohol use-related Stroke worldwide, 1990 and 2021. by Nannan Qian (10650782)

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