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用于双胞胎生存数据的遗传混合线性模型。

Genetic mixed linear models for twin survival data.

作者信息

Ha Il Do, Lee Youngjo, Pawitan Yudi

机构信息

Department of Asset Management, Daegu Haany University, Gyeongsan 712-715, Korea.

出版信息

Behav Genet. 2007 Jul;37(4):621-30. doi: 10.1007/s10519-007-9150-7. Epub 2007 Mar 31.

Abstract

Twin studies are useful for assessing the relative importance of genetic or heritable component from the environmental component. In this paper we develop a methodology to study the heritability of age-at-onset or lifespan traits, with application to analysis of twin survival data. Due to limited period of observation, the data can be left truncated and right censored (LTRC). Under the LTRC setting we propose a genetic mixed linear model, which allows general fixed predictors and random components to capture genetic and environmental effects. Inferences are based upon the hierarchical-likelihood (h-likelihood), which provides a statistically efficient and unified framework for various mixed-effect models. We also propose a simple and fast computation method for dealing with large data sets. The method is illustrated by the survival data from the Swedish Twin Registry. Finally, a simulation study is carried out to evaluate its performance.

摘要

双胞胎研究对于评估遗传或可遗传成分相对于环境成分的相对重要性很有用。在本文中,我们开发了一种方法来研究发病年龄或寿命特征的遗传力,并将其应用于双胞胎生存数据分析。由于观察期有限,数据可能会出现左截断和右删失(LTRC)情况。在LTRC设置下,我们提出了一种遗传混合线性模型,该模型允许使用一般的固定预测变量和随机成分来捕捉遗传和环境效应。推断基于分层似然(h-似然),它为各种混合效应模型提供了一个统计上有效且统一的框架。我们还提出了一种简单快速的计算方法来处理大数据集。该方法通过瑞典双胞胎登记处的生存数据进行了说明。最后,进行了一项模拟研究以评估其性能。

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