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Nonparametric Estimation of an Event-Free Survival Distribution Under Cross-Sectional Sampling

In: From Statistics to Mathematical Finance

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  • Jacobo de Uña-Álvarez

    (University of Vigo, Department of Statistics and OR & CINBIO)

Abstract

In Survival Analysis and other fields, a target of much interest is the event-free survival, which evaluates along time the probability of surviving without undergoing a certain intermediate event (recurrence, infection, and so on). Under cross-sectional sampling, only individuals in progress (alive) at the cross-section date are recruited, thus the survival times are left-truncated by the recruitment times. In this setting, there exists much literature on nonparametric estimation of the total survival, focused on the product-limit estimator for left-truncated and possibly right-censored data. However, estimation of the event-free survival has not been investigated in much detail. In this work we review this problem and we introduce a new nonparametric estimator for the event-free survival, which overcomes some of the limitations of existing approaches. Asymptotic results are discussed. A comparative numerical study is conducted.

Suggested Citation

  • Jacobo de Uña-Álvarez, 2017. "Nonparametric Estimation of an Event-Free Survival Distribution Under Cross-Sectional Sampling," Springer Books, in: Dietmar Ferger & Wenceslao González Manteiga & Thorsten Schmidt & Jane-Ling Wang (ed.), From Statistics to Mathematical Finance, chapter 0, pages 57-67, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-50986-0_4
    DOI: 10.1007/978-3-319-50986-0_4
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