  We in this paper propose a directional regression based approach for
ultrahigh dimensional sufficient variable screening with censored responses.
The new method is designed in a model-free manner and thus can be adapted to
various complex model structures. Under some commonly used assumptions, we show
that the proposed method enjoys the sure screening property when the dimension
p diverges at an exponential rate of the sample size n. To improve the marginal
screening method, the corresponding iterative screening algorithm and stability
screening algorithm are further equipped. We demonstrate the effectiveness of
the proposed method through simulation studies and a real data analysis.
