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Semiparametric regression of clustered current status data

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  • Yanqin Feng
  • Shurong Lin
  • Yang Li

Abstract

This paper discusses regression analysis of clustered current status data under semiparametric additive hazards models. In particular, we consider the situation when cluster sizes can be informative about correlated failure times from the same cluster. To address the problem, we present estimating equation-based estimation procedures and establish asymptotic properties of the resulting estimates. Finite sample performance of the proposed method is assessed through an extensive simulation study, which indicates the procedure works well. The method is applied to a motivating data set from a lung tumorigenicity study.

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  • Yanqin Feng & Shurong Lin & Yang Li, 2019. "Semiparametric regression of clustered current status data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 46(10), pages 1724-1737, July.
    • Handle: RePEc:taf:japsta:v:46:y:2019:i:10:p:1724-1737
    DOI: 10.1080/02664763.2018.1564022
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