Boomsma D I, Molenaar P C, Dolan C V
Department of Psychology, Vrije Universiteit, Amsterdam, The Netherlands.
Behav Genet. 1991 May;21(3):243-55. doi: 10.1007/BF01065818.
Parameter estimates obtained in the genetic analysis of longitudinal data can be used to construct individual genetic and environmental profiles across time. Such individual profiles enable the attribution of individual phenotypic change to changes in the underlying genetic or environmental processes and may lead to practical applications in genetic counseling and epidemiology. Simulations show that individual estimates of factor scores can be reliably obtained. Decomposition of univariate, and to a lesser extent of bivariate, phenotypic time series may yield estimates of independent individual G(t) and E(t), however, that are intercorrelated. The magnitude of these correlations depends somewhat on the autocorrelation structure of the underlying series, but to obtain completely independent estimates of genetic and environmental individual profiles, at least three measured indicators are needed at each point in time.
在纵向数据的遗传分析中获得的参数估计值可用于构建个体随时间变化的遗传和环境概况。这种个体概况能够将个体表型变化归因于潜在遗传或环境过程的变化,并可能在遗传咨询和流行病学中产生实际应用。模拟结果表明,可以可靠地获得因子得分的个体估计值。单变量以及在较小程度上双变量表型时间序列的分解可能会产生相互关联的独立个体G(t)和E(t)的估计值。这些相关性的大小在一定程度上取决于基础序列的自相关结构,但为了获得遗传和环境个体概况的完全独立估计值,每个时间点至少需要三个测量指标。