| Literature DB >> 28132157 |
Abstract
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.Keywords: Cox proportional hazards model; Crossing hazard rates; Lag effect; Survival analysis; Treatment comparison
Mesh:
Year: 2017 PMID: 28132157 DOI: 10.1007/s10985-017-9390-7
Source DB: PubMed Journal: Lifetime Data Anal ISSN: 1380-7870 Impact factor: 1.588