Copertina

Identifying the desert decision rule to assess and achieve fairness

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhang, Ping, Ying, Naiwen, Miao, Wang
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Methodology
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A generalized tetrad constraint for testing conditional independence given a latent variable
di: Ying, Naiwen, et al.
Pubblicazione: (2025)

Correcting nonignorable nonresponse bias in turnout estimation using callback data
di: Li, Xinyu, et al.
Pubblicazione: (2025)

Distributed Conditional Feature Screening via Pearson Partial Correlation with FDR Control
di: Pang, Naiwen, et al.
Pubblicazione: (2024)

Causal attribution with confidence
di: Zhang, Ping, et al.
Pubblicazione: (2025)

Counterfactual fairness for small subgroups
di: Wastvedt, Solvejg, et al.
Pubblicazione: (2023)

A stableness of resistance model for nonresponse adjustment with callback data
di: Miao, Wang, et al.
Pubblicazione: (2021)

Reliable fairness auditing with semi-supervised inference
di: Gao, Jianhui, et al.
Pubblicazione: (2025)

The risks of risk assessment: causal blind spots when using prediction models for treatment decisions
di: van Geloven, Nan, et al.
Pubblicazione: (2024)

How to achieve model-robust inference in stepped wedge trials with model-based methods?
di: Wang, Bingkai, et al.
Pubblicazione: (2024)

Neyman-Pearson and equal opportunity: when efficiency meets fairness in classification
di: Fan, Jianqing, et al.
Pubblicazione: (2023)

FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality
di: Li, Sai, et al.
Pubblicazione: (2024)

On the Identifiability of Diagnostic Classification Models
di: Fang, Guanhua, et al.
Pubblicazione: (2017)

Minority representation and fairness in network ranking: An application to school contact diary data
di: Shen, Hui, et al.
Pubblicazione: (2025)

Identifiability and Consistent Estimation for Gaussian Chain Graph Models
di: Zhao, Ruixuan, et al.
Pubblicazione: (2023)

Quantifying fair income distribution in Thailand
di: Sitthiyot, Thitithep, et al.
Pubblicazione: (2024)

Federated fairness-aware classification under differential privacy
di: Xue, Gengyu, et al.
Pubblicazione: (2026)

An information metric for comparing and assessing informative interim decisions in sequential clinical trials
di: Caruso, G., et al.
Pubblicazione: (2025)

Leveraging specificity for causal inference in observational studies
di: Miao, Wang
Pubblicazione: (2025)

Propensity score adjustment when errors in achievement measures inform treatment assignment
di: Wasserman, Joshua, et al.
Pubblicazione: (2025)

Causal Effect Identification and Inference with Endogenous Exposures and a Light-tailed Error
di: Wang, Ruoyu, et al.
Pubblicazione: (2024)

Balancing the effective sample size in prior across different doses in the curve-free Bayesian decision-theoretic design for dose-finding trials
di: Xu, Jiapeng, et al.
Pubblicazione: (2025)

Identifying Subgroup and Context Effects in Conjoint Experiments
di: Wang, Steven, et al.
Pubblicazione: (2025)

A decomposition of Fisher's information to inform sample size for developing fair and precise clinical prediction models -- part 1: binary outcomes
di: Riley, Richard D, et al.
Pubblicazione: (2024)

On the achievability of efficiency bounds for covariate-adjusted response-adaptive randomization
di: Xin, Jiahui, et al.
Pubblicazione: (2024)

Effect modification and non-collapsibility leads to conflicting treatment decisions: a review of marginal and conditional estimands and recommendations for decision-making
di: Phillippo, David M., et al.
Pubblicazione: (2024)

DeepKriging on the global Data
di: Huang, Hao-Yun, et al.
Pubblicazione: (2026)

A maximin optimal approach for sampling designs in two-phase studies
di: Wang, Ruoyu, et al.
Pubblicazione: (2023)

A decomposition of Fisher's information to inform sample size for developing fair and precise clinical prediction models -- Part 2: time-to-event outcomes
di: Riley, Richard D, et al.
Pubblicazione: (2025)

A decomposition of Fisher's information to inform sample size for developing or updating fair and precise clinical prediction models -- Part 3: continuous outcomes
di: Whittle, Rebecca, et al.
Pubblicazione: (2025)

Robust measures of dispersion for circular data with an anomaly detection rule
di: Demni, Houyem, et al.
Pubblicazione: (2026)

Risk-based decision making: estimands for sequential prediction under interventions
di: Luijken, Kim, et al.
Pubblicazione: (2023)

A theory of ROC analysis of rule-out and rule-in diagnostics with applications to mammography data
di: Mastrianni, Michelle, et al.
Pubblicazione: (2026)

Robust Spatial-Sign-Based Testing of High-Dimensional Alpha in Conditional Factor Models
di: Zhao, Ping, et al.
Pubblicazione: (2026)

Identifiable and interpretable nonparametric factor analysis
di: Xu, Maoran, et al.
Pubblicazione: (2023)

Identifiability of Latent Class Models with Covariates
di: Ouyang, Jing, et al.
Pubblicazione: (2021)

Tripartite models for estimating the value of drug candidates and decision tools
di: Mellnik, John, et al.
Pubblicazione: (2025)

A Two-Step Test to Identify Zero-Inflated Biomarkers in Early-Phase Clinical Trials
di: Xi, Nan Miles, et al.
Pubblicazione: (2025)

MoDaH achieves rate optimal batch correction
di: Cao, Yang, et al.
Pubblicazione: (2025)

Integrating complex selection rules into the latent overlapping group Lasso for constructing coherent prediction models
di: Wang, Guanbo, et al.
Pubblicazione: (2022)

Identifiability and Inference for Generalized Latent Factor Models
di: Cui, Chengyu, et al.
Pubblicazione: (2025)