Two types of problems are considered in this proposal: (i) nonparametric regression analysis of censored data and (ii) software development for censored data problems. Under (i) statistical methodology will be developed and investigated for the analysis of heterogeneous censored data. While procedures are available for this problem, they suffer from several deficiencies. First, assumptions concerning the underlying hazard function are required (proportional or accelerated hazards or some particular distributional form). Second, survival is assumed to be effected via a linear combination of covariates. Thus, deviations in the data from these assumptions can lead to misleading conclusions. Thirdly, certain procedures can be infeasible for problems with more than two covariates. By integrating ideas from projection pursuit regression and the nonparametric estimation of the hazard function, these difficulties can be avoided and one can thereby develop completely nonparametric regression technology. Under (ii) efficient and portable software will be developed to accompany this methodology.