Objectives: To explore the applicability of two level variance component model in research on variability between interviewers.
前言：目的：探讨两水平方差成份模型在评价调查者间变异的应用价值。
Variance component model of the random effects of covariance matrix unit for the "Linear model introduction" matrix has been studied.
方差分量模型的随机效应的协方差为单位阵时《线性模型引论》已进行研究。
Methods Two-level variance component model was used by MLWIN2.0 to evaluate the reliability of satisfaction scale within investigators.
方法采用软件MLWIN2．0，运用两水平方差成分模型评价满意度量表调查员间的信度；
Methods We applied generalized linear mixed models for the nuclear family data to set up the genetic variance component model and estimated parameters using MCMC.
将广义线性混合模型应用于核心家系资料建立遗传方差分量模型，运用MCMC方法进行参数估计。
Conclusion:In the condition of unrepeated measurement, the variability between interviewers can be estimated by fitting two level variance component model for normally distributed data.
结论：对于问卷项目的应答为连续性正态分布的数据，在拟合重复调查的情形下，可以采用两水平方差成份模型评价问卷项目应答的信度。
Spectral decomposition estimators of variance component matrix in mixed linear model are generalized to multivariate mixed linear model.
考虑含有两个方差分量矩阵的多元混合模型，将一元混合模型下的谱分解估计推广到多元模型下。
Linear models are especially important statistical models, including linear regression model, variance and analysis, covariance and analysis, and variance and component one etc.
线性模型是很重要的一类统计模型，它包括线性回归模型、方差分析模型、协方差分析模型和方差分量模型等等。
Linear models are especially important statistical models, including linear regression model, variance and analysis, covariance and analysis, and variance and component one etc.
线性模型是很重要的一类统计模型，它包括线性回归模型、方差分析模型、协方差分析模型和方差分量模型等等。
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