加法性模型在左截斷右設限資料結構下之擬概似函數估計

Abstract

本文主要探討左截斷右設限的存活資料並利用此資料來建構加法性的模型。本文將提供極大化擬概似函數的方式得到參數與非參數的估計量。並且從模擬中可以發現本文提及之方法所得到的標準誤會比文獻還要小。

This study focuses on investigating the additive hazards model with left-truncated and right-censored data. More specifically, we develop a pseudo likelihood estimation approach for the parameters of primary interests. Through the conducted simulations, the proposed estimator is further found to outperform the existing competitors in the literature.