Using Semiparametric Risk Sets for the Analysis of Cross-Sectional Duration Data

  • Mei-Cheng Wang


It is a common sampling scheme that individuals in a prospective cohort study are selected using a cross-sectional criterion. Suppose an epidemic process is characterized by three chronologically ordered events, termed event-A, -B, and -C. Suppose a prospective cohort only recruits individuals who have experienced event-A and have not experienced event-C. Therefore data from those who have experienced event-C prior to the time of recruitment are excluded from the analysis. In this paper we consider the situation when the time from event-A to event-B is treated as the major outcome variable, and interests are focused on nonparametric or semiparametric models for this variable. A class of semiparametric risk sets is introduced for constructing a variety of statistical methods. The general relationship between cross-sectional duration data and intercepted renewal data is characterized. The application of the proposed methods to intercepted renewal data is discussed. An example in which the event-ABC process corresponds to (HIV-infection, first diagnosis of AIDS, death) is presented.


Under Sampling Calendar Time Semiparametric Model Epidemic Process Reporting Delay 
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Copyright information

© Springer Science+Business Media New York 1992

Authors and Affiliations

  • Mei-Cheng Wang
    • 1
  1. 1.Department of BiostatisticsJohns Hopkins University School of Hygiene and Public HealthBaltimoreUSA

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