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Interval-censored parametric regression survival models and the analysis of longitudinal trials

机译:区间删失的参数回归生存模型及纵向试验分析

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This paper develops interval censoring likelihood methods in the context of parametric proportional hazard (PH) and non-PH regression models in the longitudinal study setting to reanalyze the medical research council's randomized controlled trial of teletherapy in age-related macular degeneration. We compare the performance of the interval censoring likelihood with proxy likelihoods that were used to analyze the original data. It is shown, analytically, that the use of such proxy likelihoods in selected PH models leads to biased estimators. Such estimators are artificially precise; further, the magnitude of their percentage bias is quantified in a data-directed simulation study. For non-PH models, we demonstrate that these results obtained from PH models do not hold uniformly and explain the implications of this finding for the reanalysis of proxy likelihood trial data. Our final analysis, of the age-related macular degeneration trial data, based on fitting PH and non-PH models, reassuringly confirms the published findings from the original trial.
机译:本文在纵向研究背景下,在参数比例风险(PH)和非PH回归模型的背景下开发了间隔检查似然法,以重新分析医学研究委员会针对年龄相关性黄斑变性进行远程治疗的随机对照试验。我们将间隔检查似然度的性能与用于分析原始数据的代理似然度进行比较。从分析上显示,在选定的PH模型中使用此类替代可能性会导致估计量有偏差。这样的估计是人为地精确的。此外,在以数据为导向的模拟研究中量化了其百分比偏差的大小。对于非PH模型,我们证明从PH模型获得的这些结果不一致,并解释了这一发现对代理似然试验数据的重新分析的意义。我们基于适合的PH和非PH模型对与年龄相关的黄斑变性试验数据的最终分析,可以肯定地证实原始试验的已发表结果。

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