Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA.
Stat Methods Med Res. 2010 Apr;19(2):147-65. doi: 10.1177/0962280208094278. Epub 2008 Sep 2.
As a type of multivariate survival data, multistate models have a wide range of applications, notably in cancer and infectious disease progression studies. In this article, we revisit the problem of estimation of state occupation, entry and exit times in a multistate model where various estimators have been proposed in the past under a variety of parametric and non-parametric assumptions. We focus on two non-parametric approaches, one using a product limit formula as recently proposed in Datta and Sundaram(1) and a novel approach using a fractional risk set calculation followed by a subtraction formula to calculate the state occupation probability of a transient state. A numerical comparison between the two methods is presented using detailed simulation studies. We show that the new estimators have lower statistical errors of estimation of state occupation probabilities for the distant states. We illustrate the two methods using a pubertal development data set obtained from the NHANES III.(2).
作为一种多元生存数据分析方法，多状态模型应用广泛，尤其是在癌症和传染病进展研究中。在本文中，我们重新研究了在多状态模型中估计状态占用、进入和退出时间的问题，过去已经提出了各种基于参数和非参数假设的估计方法。我们重点关注两种非参数方法，一种使用最近在 Datta 和 Sundaram(1)中提出的乘积限公式，另一种使用分数风险集计算，然后使用减法公式计算瞬态状态的状态占用概率。使用详细的模拟研究对两种方法进行了数值比较。我们表明，新的估计器在估计遥远状态的状态占用概率时具有更低的统计误差。我们使用来自 NHANES III 的青春期发育数据集(2)说明了这两种方法。
