Preference for the EIA – conjoint results. 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 attribute table. 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. …”

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. …”

Join-point regression analysis of the statistically significant linear increase in use of antidementia and antipsychotics during the observed time period. by Jelena Filimonovic (22305307)

Knockdown of MRN complex decreases HBV cccDNA level. by Kaitao Zhao (3617825)

Knockdown of MRN complex decreases HBV cccDNA level. by Kaitao Zhao (3617825)

The Date. by Chengyuan Hao (21615653)

“…Secondly, the daily minimum and maximum temperatures increased significantly, which were 0.395°C/10a and 0.200°C/10a respectively<b>—</b>less than the national mean. …”

Variation curve of the extreme temperature index. by Chengyuan Hao (21615653)

“…Secondly, the daily minimum and maximum temperatures increased significantly, which were 0.395°C/10a and 0.200°C/10a respectively<b>—</b>less than the national mean. …”

The mean number of the emerged <i>D. melanogaster</i> adults. Mean number (±SE) of emerged adults and average percentage (±SE) of the residual fertility at the different treatment... by Flavia Cerasti (21655934)

Functional analysis of a <i>kh</i>^<i>w</i> mutant mosquitoes. by Si Yu Zhao (19544793)

CIE L*a*b* color space values of urine measured by a spectrophotometer showed significant correlations with Uturb as observed through visual examination. by Jingnan Liu (2219029)

“…<p>(A) The increase in Uturb was significantly correlated with a decrease in urine brightness (L*). …”

Changes in the color parameters of cherry shrimp (<i>N</i>. <i>davidi</i> var. red) in different feed treatment groups^a over a 56-day period (mean ± SD, <i>n</i> = 20). by Wei-Wei Hou (3405947)

Quantification of bacterial adhesion revealed a significant decrease in the adhesion of <i>S. aureus</i>, <i>S. epidermidis</i>, and <i>P. aeruginosa</i> on blotted corneas of mice treated with 0.5% bupivacaine (BUP) combined with topical (TOP) application, following subconjunctival injection (SCI) of CGRP, 24 hours before the final BUP treatment (day 14) and again one hour prior to the final bupivacaine injection on day 15. by Ananya Datta (19932144)

Maximum likelihood estimates of trans-log mean stochastic function. by James Anaba Akolgo (14129379)

Predictors used in the modelling analysis. The ‘Snail count’ model refers to the Generalised Linear Mixed Model (GLMM) used to model snail counts, ‘Prevalence’ refers to the diseas... by Roland Proud (11764892)

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Summary of post-treatment disease course measures from MDMA-AT publications. by Filip Stanicic (17808254)

Subjects: