Published 2004 in Advances in Survival Analysis, Chapter 35, pp. 625-643 (eds. N. Balakrishnan and C.R. Rao), Handbook of Statistics, 23, Elsevier North Holland.


Researchers working with survival data are by now adept at handling issues associated with incomplete data, particular those associated with various forms of censoring. An extreme form of interval censoring, known as current status observation, refers to situations where the only available information on a survival random variable T is whether or not T exceeds a random independent monitoring time C. This article contains a brief review of the extensive literature on the analysis of current status data, discussing the implications of response-based sampling on these methods. The majority of the paper introduces some recent extensions of these ideas to more complex forms of survival data including, competing risks, multivariate survival data, and general counting processes. Our comments are largely focused on nonparametric techniques where the form of the distribution function, or survival curve, associated with T, is left unspecified. Modern theory of efficient estimation in semiparametric models has allowed substantial progress on many questions regarding estimation based on current status data in these extended formats; we also highlight remaining open questions of interest.


Epidemiology | Statistical Methodology | Statistical Theory | Survival Analysis