Scholarlink

<p>In this paper, we investigate the subgroup analysis for the right censored data based on the individualized proportional hazard regression model. With the fused LASSO, SCAD and MCP penalties for the difference of individualized effect parameters, we establish the penalized partial likelihood function. By the local approximation of penalty function, the fused penalty term in loss function is transformed into a quadratic form and the Newton–Raphson algorithm can be easily used to optimize it. Under some regular conditions, we present the oracle results for the subgroup detection. We evaluate our proposed methodology through some simulation studies and a real data analysis.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Fusion penalized subgroup analysis for right censored data based on cox model with local approximation

  • 期刊论文

  • 发表日期：

    2025年2月28日

查看全文
  • Fei Wang,
  • Yiwei Chen,
  • Jianbo Li,
  • Qin Zhou,
  • Riquan Zhang

摘要

In this paper, we investigate the subgroup analysis for the right censored data based on the individualized proportional hazard regression model. With the fused LASSO, SCAD and MCP penalties for the difference of individualized effect parameters, we establish the penalized partial likelihood function. By the local approximation of penalty function, the fused penalty term in loss function is transformed into a quadratic form and the Newton–Raphson algorithm can be easily used to optimize it. Under some regular conditions, we present the oracle results for the subgroup detection. We evaluate our proposed methodology through some simulation studies and a real data analysis.