Semiparametric regression modeling of the global percentile outcome
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Publication:2676903
DOI10.1016/j.jspi.2022.06.009OpenAlexW4283390431MaRDI QIDQ2676903
Jing Ning, Xuming He, Barbara C. Tilley, Ruosha Li, Xiang-Yu Liu
Publication date: 28 September 2022
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2022.06.009
rank-sumnon-smooth objective functiontransformed linear modelglobal percentile outcomemonotonic index model
Cites Work
- Non-parametric analysis of a generalized regression model. The maximum rank correlation estimator
- Rank estimators for monotonic index models
- Maximal inequalities for degenerate \(U\)-processes with applications to optimization estimators
- Regression analysis under link violation
- A simple resampling method by perturbing the minimand
- Global rank tests for multiple, possibly censored, outcomes
- Survival Analysis With Quantile Regression Models
- Concordance-Assisted Learning for Estimating Optimal Individualized Treatment Regimes
- The Limiting Distribution of the Maximum Rank Correlation Estimator
- Adjusting O'Brien's Test to Control Type I Error for the Generalized Nonparametric Behrens–Fisher Problem
