Outcome-dependent sampling design and inference for Cox's proportional hazards model

DOI10.1016/j.jspi.2016.05.001zbMath1353.62110OpenAlexW2402440087WikidataQ37577759 ScholiaQ37577759MaRDI QIDQ313103

Jianwen Cai, Dale P. Sandler, Haibo Zhou, Yan Yan Liu, Ji-Chang Yu

Publication date: 9 September 2016

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.2016.05.001

zbMATH Keywords

empirical processoptimal allocationoutcome-dependent sampling

Mathematics Subject Classification ID

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

Related Items

Accelerated failure time model for data from outcome-dependent sampling ⋮ Statistical inference for the accelerated failure time model under two-stage generalized case–cohort design ⋮ A quadratic upper bound algorithm for regression analysis of credit risk under the proportional hazards model with case-cohort data ⋮ Regression analysis for outcome-dependent sampling design under the covariate-adjusted additive hazards model ⋮ Optimal generalized case-cohort analysis with accelerated failure time model ⋮ Generalized case-cohort and inference for Cox’s model with parameter constraints

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