Statistical Methodology 9 (2012) 501–512 Contents lists available at SciVerse ScienceDirect Statistical Methodology journal homepage: www.elsevier.com/locate/stamet Nonparametric estimators for a survivor function of paired recurrent events P.G. Sankaran a,* , M. Manoharan b , P. Anisha a a Department of Statistics, Cochin University of Science and Technology, Cochin-682 022, India b Department of Statistics, University of Calicut, Malappuram-673 635, Calicut, India article info Article history: Received 24 November 2009 Received in revised form 5 September 2011 Accepted 10 January 2012 Keywords: Recurrent event data Bivariate survivor function Nonparametric estimation Dabrowska’s estimator abstract Recurrent event data arise in longitudinal studies where each study subject may experience multiple events during the follow- up. In many situations in survival studies, pairs of individuals can potentially experience recurrent events. The analysis of such data is not straightforward as it involves two kinds of dependences, namely, dependence between the individuals in the same pair and dependence among a sequence of pairs. In the present paper, we introduce a new stochastic model for the analysis of such recurrent event data. Nonparametric estimators for a bivariate survivor function are developed. Asymptotic properties of the estimators are discussed. Simulation studies are carried out to assess the finite sample properties of the estimator. We illustrate the procedure with real life data on eye disease. © 2012 Elsevier B.V. All rights reserved. 1. Introduction In survival analysis, many applications involve repeated events where a study subject may experiences any number of events over a follow-up time. Such data are called repeated event data or recurrent event data. Recurrent event data arise in a wide variety of situations, including biomedicine, public health, psychology, engineering, demography and economics. Examples of recurrent events in life length studies are repeated hospitalizations of patients with chronic diseases and the breakdown of mechanical or electrical systems. The analysis of recurrent event data using statistical methods is, therefore, a topic of interest in survival studies. Two different time scales are usually employed in the literature for the analysis of recurrent events. The two types are the times since entering the study and the times since the last event. For the * Corresponding author. E-mail addresses: sankaranpg@yahoo.com, sankaran.p.g@gmail.com (P.G. Sankaran). 1572-3127/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.stamet.2012.01.001