Confidence intervals for high-dimensional Cox models

Authors :: Yi Yu
Jelena Bradic
Richard J. Samworth
Samworth, Richard [0000-0003-2426-4679]
Apollo - University of Cambridge Repository
Source :: Statistica Sinica, vol 31, iss 1, STATISTICA SINICA, vol 31, iss 1, Yu, Y, Bradic, J & Samworth, R J 2021, ' Confidence intervals for high-dimensional Cox models ', Statistica Sinica, vol. 31, no. 1, pp. 243-267 . https://doi.org/10.5705/ss.202018.0247
Publication Year :: 2021
Publisher :: Statistica Sinica (Institute of Statistical Science), 2021.
Abstract: The purpose of this paper is to construct confidence intervals for the regression coefficients in high-dimensional Cox proportional hazards regression models where the number of covariates may be larger than the sample size. Our debiased estimator construction is similar to those in Zhang and Zhang (2014) and van de Geer et al. (2014), but the time-dependent covariates and censored risk sets introduce considerable additional challenges. Our theoretical results, which provide conditions under which our confidence intervals are asymptotically valid, are supported by extensive numerical experiments.<br />Comment: 36 pages, 1 figure