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Non‐parametric Estimation of a Survival Function with Two‐stage Design Studies

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  • GANG LI
  • CHI‐HONG TSENG

Abstract

. The two‐stage design is popular in epidemiology studies and clinical trials due to its cost effectiveness. Typically, the first stage sample contains cheaper and possibly biased information, while the second stage validation sample consists of a subset of subjects with accurate and complete information. In this paper, we study estimation of a survival function with right‐censored survival data from a two‐stage design. A non‐parametric estimator is derived by combining data from both stages. We also study its large sample properties and derive pointwise and simultaneous confidence intervals for the survival function. The proposed estimator effectively reduces the variance and finite‐sample bias of the Kaplan–Meier estimator solely based on the second stage validation sample. Finally, we apply our method to a real data set from a medical device postmarketing surveillance study.

Suggested Citation

  • Gang Li & Chi‐Hong Tseng, 2008. "Non‐parametric Estimation of a Survival Function with Two‐stage Design Studies," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(2), pages 193-211, June.
  • Handle: RePEc:bla:scjsta:v:35:y:2008:i:2:p:193-211
    DOI: 10.1111/j.1467-9469.2007.00581.x
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