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Clustered Survival Data with Left-truncation

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  • Frank Eriksson
  • Torben Martinussen
  • Thomas H. Scheike

Abstract

type="main" xml:id="sjos12157-abs-0001"> Left-truncation occurs frequently in survival studies, and it is well known how to deal with this for univariate survival times. However, there are few results on how to estimate dependence parameters and regression effects in semiparametric models for clustered survival data with delayed entry. Surprisingly, existing methods only deal with special cases. In this paper, we clarify different kinds of left-truncation and suggest estimators for semiparametric survival models under specific truncation schemes. The large-sample properties of the estimators are established. Small-sample properties are investigated via simulation studies, and the suggested estimators are used in a study of prostate cancer based on the Finnish twin cohort where a twin pair is included only if both twins were alive in 1974.

Suggested Citation

  • Frank Eriksson & Torben Martinussen & Thomas H. Scheike, 2015. "Clustered Survival Data with Left-truncation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(4), pages 1149-1166, December.
    • Handle: RePEc:bla:scjsta:v:42:y:2015:i:4:p:1149-1166
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    File URL: http://hdl.handle.net/10.1111/sjos.12157
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    References listed on IDEAS

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    1. Christian Bressen Pipper & Torben Martinussen, 2004. "An estimating equation for parametric shared frailty models with marginal additive hazards," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 207-220, February.
    2. Gerard J. van den Berg & Bettina Drepper, 2016. "Inference for Shared-Frailty Survival Models with Left-Truncated Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1075-1098, June.
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    4. Christian Bressen Pipper & Torben Martinussen, 2003. "A Likelihood Based Estimating Equation for the Clayton–Oakes Model with Marginal Proportional Hazards," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(3), pages 509-521, September.
    5. E. T. Parner, 2001. "A Composite Likelihood Approach to Multivariate Survival Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(2), pages 295-302, June.
    6. D. Zeng & D. Y. Lin, 2007. "Maximum likelihood estimation in semiparametric regression models with censored data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(4), pages 507-564, September.
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    Cited by:

    1. Marie Böhnstedt & Jutta Gampe & Monique A. A. Caljouw & Hein Putter, 2023. "Incorporating delayed entry into the joint frailty model for recurrent events and a terminal event," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(3), pages 585-607, July.

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