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Interval Censored Survival Data: A Review of Recent Progress

  • Conference paper
Proceedings of the First Seattle Symposium in Biostatistics

Part of the book series: Lecture Notes in Statistics ((LNS,volume 123))

Abstract

We review estimation in interval censoring models, including nonparametric estimation of a distribution function and estimation of regression models. In the nonparametric setting, we describe computational procedures and asymptotic properties of the nonparametric maximum likelihood estimators. In the regression setting, we focus on the proportional hazards, the proportional odds and the accelerated failure time semiparametric regression models. Particular emphasis is given to calculation of the Fisher information for the regression parameters. We also discuss computation of the regression parameter estimators via profile likelihood or maximization of the semiparametric likelihood, distributional results for the maximum likelihood estimators, and estimation of (asymptotic) variances. Some further problems and open questions are also reviewed.

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Author information

Authors and Affiliations

  1. Department Of Statistics and Acturial Science, University of Iowa, Iowa City, Iowa, 52242, USA

    Jian Huang

  2. University of Washington Statistics, Box 354322, Seattle, Washington, 98195-4322, USA

    Jon A. Wellner

Authors
  1. Jian Huang
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  2. Jon A. Wellner
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Editor information

Editors and Affiliations

  1. Department of Biostatistics, School of Public Health and Community Medicine, University of Washington, Box 357232, Seattle, WA, 91895, USA

    D. Y. Lin  & T. R. Fleming  & 

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Huang, J., Wellner, J.A. (1997). Interval Censored Survival Data: A Review of Recent Progress. In: Lin, D.Y., Fleming, T.R. (eds) Proceedings of the First Seattle Symposium in Biostatistics. Lecture Notes in Statistics, vol 123. Springer, New York, NY. https://doi.org/10.1007/978-1-4684-6316-3_8

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  • DOI: https://doi.org/10.1007/978-1-4684-6316-3_8

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-94992-5

  • Online ISBN: 978-1-4684-6316-3

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