Evaluation of the treatment time-lag effect for survival data
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Medical treatments often take a period of time to reveal their impact on subjects, which is the so-called time-lag effect in the literature. In the survival data analysis literature, most existing methods compare two treatments in the entire study period. In cases when there is a substantial time-lag effect, these methods would not be effective in detecting the difference between the two treatments, because the similarity between the treatments during the time-lag period would diminish their effectiveness. In this paper, we develop a novel modeling approach for estimating the time-lag period and for comparing the two treatments properly after the time-lag effect is accommodated. Theoretical arguments and numerical examples show that it is effective in practice.
KeywordsCox proportional hazards model Crossing hazard rates Lag effect Survival analysis Treatment comparison
The authors thank the editor and two referees for their valuable comments which greatly improved the quality of this paper.
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