Methods to estimate bivariate survival function under *bivariate* censoring I am looking at the relation between two time-to-event variables subject to censoring. The seminal work from Lin and Ying is unfortunately paywalled (https://www.jstor.org/stable/2337178), but I understand the major limitation is that the general method only admits univariate censoring. Has any work dealt with the estimation of a bivariate survival function in the case of bivariate censoring that doesn't require parametric models for the response and imputation?

Dabrowska discusses this problem, and Prentice and Cai.  Oakes has also proposed semiparametric models, where the marginal survival functions are arbitrary but the dependence is controlled by a single parameter.
