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Models for interval censoring and simulation-based inference for lifetime distributions

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  • J. F. Lawless
  • Denise Babineau

Abstract

Interval-censored lifetime data arise when individuals in a study are inspected intermittently so that a lifetime is observed to lie between two successive times. In settings where only these two times are available, methods exist for nonparametric or parametric estimation of lifetime distributions. However, there has been virtually no discussion of how inspection processes may be estimated or identified. Such estimates are needed if one is to generate interval-censored data by simulation. This paper identifies which aspects of an independent inspection process are estimable from interval-censored data, and shows how to obtain nonparametric estimates. The results allow interval-censored data from any specified distribution to be generated, and give new simulation procedures for estimation or testing. A new omnibus goodness-of-fit test is introduced. Copyright 2006, Oxford University Press.

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  • J. F. Lawless & Denise Babineau, 2006. "Models for interval censoring and simulation-based inference for lifetime distributions," Biometrika, Biometrika Trust, vol. 93(3), pages 671-686, September.
    • Handle: RePEc:oup:biomet:v:93:y:2006:i:3:p:671-686
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    File URL: http://hdl.handle.net/10.1093/biomet/93.3.671
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    Cited by:

    1. Soumya Roy & Biswabrata Pradhan, 2023. "Inference for log‐location‐scale family of distributions under competing risks with progressive type‐I interval censored data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(2), pages 208-232, May.

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