We consider the inverse problem of estimating a survival distribution when the survival times are only observed to be in one of the intervals of a random bisection of the time axis. We are particularly interested in the case that high-dimensional and/or time-dependent covariates are available, and/or the survival events and censoring times are only conditionally independent given the covariate process. The method of estimation consists of regularizing the survival distribution by taking the primitive function or smoothing, estimating the regularized parameter by using estimating equations, and finally recovering an estimator for the parameter of interest.
Keywords: semiparametric model; curse of dimensionality; isotonic estimation; censoring; coarsening-at-random
Published Online: 2006-10-10
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
