Robust inference for the proportional hazards model with two-phase cohort sampling data

DOI10.1016/j.spl.2019.05.014zbMath1427.62133OpenAlexW2952942052WikidataQ127717847 ScholiaQ127717847MaRDI QIDQ2322675

Ming Zheng, Wen Yu, Chanjuan Lin, Mingzhe Wu

Publication date: 5 September 2019

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2019.05.014

zbMATH Keywords

robust inferenceinverse probability weightingcohort studysampling designscase-cohort samplingmisspecified Cox proportional hazards model

Mathematics Subject Classification ID

Nonparametric robustness (62G35) Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)

Cites Work

• Unnamed Item
• Statistical estimation in the proportional hazards model with risk set sampling
• Generalized Case–cohort Sampling
• End-point sampling
• The Robust Inference for the Cox Proportional Hazards Model
• Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates
• Properties of Proportional-Hazards Score Tests under Misspecified Regression Models
• A case-cohort design for epidemiologic cohort studies and disease prevention trials
• Misspecified proportional hazard models
• Efficient estimation for case-cohort studies
• Case-cohort and case-control analysis with Cox's model
• Efficient Estimation of Semiparametric Transformation Models for Two-Phase Cohort Studies
• Separate sample logistic discrimination

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