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Two-sample test based on empirical likelihood ratio under semi-competing risks data

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  • Jin-Jian Hsieh
  • Jyun-Peng Li

Abstract

This article considers the two-sample testing problem of the survival function of the non terminal event time under semi-competing risks data. The empirical likelihood function is constructed for the survival function estimation of the non terminal event time, then maximize it by the PSO (Particle swarm optimization) algorithm to obtain the MLE. For the testing problem, the article develops the empirical likelihood ratio test to compare the two survival curves. From simulation studies, it shows the performance of the proposed approaches is good. Finally, a real data analysis is presented for illustration.

Suggested Citation

  • Jin-Jian Hsieh & Jyun-Peng Li, 2022. "Two-sample test based on empirical likelihood ratio under semi-competing risks data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(10), pages 3301-3311, May.
    • Handle: RePEc:taf:lstaxx:v:51:y:2022:i:10:p:3301-3311
    DOI: 10.1080/03610926.2020.1793363
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