Frontier analysis for the potential for improvement in reducing the burden of IBD among WCBA across 204 countries and regions. by Jiefeng Zhao (9090305)

Subjects:

RTA408 significantly reduces RGCs loss. by Hongmei Qian (538647)

Subjects:

RTA408 significantly reduces RGCs loss in glaucoma. by Hongmei Qian (538647)

Subjects:

Cardiac performance and hemolymph distribution are significantly reduced upon valve malformation. by Christian Meyer (6035)

The reduced virulence of Δalta1 mutants is not primarily due to a decrease in growth. by Shuhuan Zhang (748003)

Transepithelial resistance of NHBE decreases significantly after PAA exposure. by Ellie S. Burns (21246537)

Introgression decreases allelic shuffling. by Enrique J. Schwarzkopf (6579275)

EF-24 treatment significantly reduces cell viability in leukemia cell lines. by Ajeet P. Singh (22298432)

Subjects:

Frequency of tobacco smoking among smokers. by Prasanna Herath (20714794)

Subjects:

Correlation of lung function parameters with smoking variables. by Prasanna Herath (20714794)

Subjects:

Anthropometric characteristics of smokers and non-smokers. by Prasanna Herath (20714794)

Subjects:

Respiratory clinical characteristics of smokers and non-smokers. by Prasanna Herath (20714794)

Subjects:

Effect of the smoking factor on lung function parameters (FVC, FEV1, PEF, FEF 25_75). by Prasanna Herath (20714794)

Subjects:

Lung function parameters between smokers and non-smokers. by Prasanna Herath (20714794)

Subjects:

Increased or reduced ATGL-1 activity does not significantly change <i>N. parisii</i> growth. by Hala Tamim El Jarkass (16625309)

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. …”

Marginal means – 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. …”

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. …”