Bootstrap pointwise confidence intervals for covariate-adjusted survivor functions in the Cox model

Constantin Ruhe ()
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Constantin Ruhe: Goethe University Frankfurt

Stata Journal, 2019, vol. 19, issue 1, 185-199

Abstract: Survival functions are a common visualization of predictions from the Cox model. However, neither Stata’s stcurve command nor the community-contributed scurve tvc command allows one to estimate confidence intervals. In this article, I discuss how bootstrap confidence intervals can be formed for covariate-adjusted survival functions in the Cox model. The new bsurvci com- mand automates this procedure and allows users to visualize the results. bsurvci enables one to estimate uncertainty around survival functions estimated from Cox models with time-varying coefficients, a capability that was not previously avail- able in Stata. Furthermore, it provides Stata users with an additional option for survival estimates from Cox models with proportional hazards by allowing them to choose between bootstrap confidence intervals using bsurvci and asymptotic confidence intervals from an existing community-contributed command, survci. Because asymptotic confidence intervals make distributional assumptions when constructing confidence intervals, the bootstrap procedure proposed in this article provides a nonparametric alternative.

Keywords: bsurvci; scurve tvc; stcox; tvc(); survci; confidence intervals; bootstrap; Cox model; proportional hazards; time-varying coefficients; survival function (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1177/1536867X19830915

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