Testing additivity in nonparametric regression under random censorship
  In this paper, we are concerned with nonparametric estimation of the multivariate regression function in the presence of right censored data. More precisely, we propose a statistic that is shown to be asymptotically normally distributed under the additive assumption, and that could be used to test for additivity in the censored regression setting. 
Mohammed Debbarh and Vivian Viallon