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Non-parametric estimation with doubly censored data

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  • Guadalupe Gomez
  • M. Luz Calle

Abstract

Data from longitudinal studies in which an initiating event and a subsequent event occur in sequence are called 'doubly censored' data if the time of both events is interval-censored. This paper is concerned with using doubly censored data to estimate the distribution function of the so-called 'duration time', i.e. the elapsed time between the originating event and the subsequent event. The paper proposes a generalization of the Gomez and Lagakos two-step method for the case where both the time to the initiating event and the duration time are continuous. This approach is applied to estimate the AIDS-latency time from a haemophiliacs cohort.

Suggested Citation

  • Guadalupe Gomez & M. Luz Calle, 1999. "Non-parametric estimation with doubly censored data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(1), pages 45-58.
    • Handle: RePEc:taf:japsta:v:26:y:1999:i:1:p:45-58
    DOI: 10.1080/02664769922647
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    Cited by:

    1. Patrice Takam Soh & Eugène-Patrice Ndong Nguéma & Henri Gwet & Michel Ndoumbè-Nkeng, 2013. "Smooth estimation of a lifetime distribution with competing risks by using regular interval observations: application to cocoa fruits growth," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(5), pages 741-760, November.
    2. Pao-sheng Shen, 2011. "Nonparametric estimation with doubly censored and truncated data," Computational Statistics, Springer, vol. 26(1), pages 145-157, March.

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