TheKaplan-Meier Integral in the Presenceof Covariates:AReview

نویسندگان

  • Thomas A. Gerds
  • Jan Beyersmann
  • Liis Starkopf
  • Sandra Frank
  • Mark J. van der Laan
  • Martin Schumacher
چکیده

Here, T is the time of an event and Z a p-dimensional vector of covariates, φ a square integrable function, and F(t | z) = P (T ≤ t | Z = z) and H( dz) = P (Z ∈ dz) denote the conditional survival distribution and the marginal law of Z , respectively. For example, θ(I {t > t∗}) is the marginal survival probability at time t∗, θ(I {t > t∗, z1 > z∗ 1}) the bivariate distribution at (t∗, z∗ 1) (Akritas 1994), and θ([I {t > t∗} − m(t∗|z)]2) the expected Brier score of a regression model m which predicts survival at time t∗ conditional on the covariates (Graf et al. 1999). In the absence of covariates, using the integrand φs(t) = exp(st) in (2.1) has been used for expressing the moment generating function of multi-state survival times (Hudson et al. 2014).

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تاریخ انتشار 2017