Analysis of survival data with missing measurements of a time-dependent binary covariate.
Analysis of survival data with missing measurements of a time-dependent binary covariate.
复制标题
对缺少时间依赖性二元协变量测量值的生存数据进行分析。
DOI：
10.1081/bip-120019270
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
Davis,BarryR
中科院分区：
文献类型：
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作者：
Halabi,Susan;Wun,Chuan-Chuan;Davis,BarryR
这项研究的目的是利用比例风险模型中的最后一次观察，调查二元时间依赖协变量的数量和时间对偏差的影响。在截尾率、时变协变量的转移概率、样本量和协变量的对数风险比等不同假设下，我们实证检验了样本个数和时间对协变量估计偏差的影响。使用了老年收缩期高血压项目的一个例子。收缩压对存活率影响的推断受收缩压测量的次数和时间的强烈影响。
The objective of this study was to investigate the influence of the number and timing of a binary time-dependent covariate on the bias using the last-observation carried forward in the proportional hazards model. Under various assumptions of censoring rates, transition probabilities of the time-dependent covariate, sample size, and the log hazard-ratio for the covariate, we empirically examined the impact that the number and timing have on the bias of the estimator of the covariate. An example from the Systolic Hypertension in the Elderly Program was used. Inference on the effect of systolic blood pressure on survival is strongly affected by the number and timing of systolic blood measurements.