findFactorResidualVar(simsem)
findFactorResidualVar()所属R语言包:simsem
Find factor residual variances from regression coefficient matrix, factor (residual) correlations, and total factor variances
从回归系数矩阵,因子(剩余)的相关性,与全要素差异的因素剩余的差异
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Find factor residual variances from regression coefficient matrix, factor (residual) correlation matrix, and total factor variances for latent variable models. In the path analysis model, this function will find indicator residual variances from regression coefficient, indicator (residual) correlation matrix, and total indicator variances.
从回归系数矩阵,因子(剩余)相关矩阵和全要素潜变量模型的差异的因素剩余的差异。在路径分析模型,这个函数会发现从回归系数指标(剩余)相关矩阵和总指标差异的指标剩余的差异。
用法----------Usage----------
findFactorResidualVar(beta, corPsi, totalVarPsi = NULL)
参数----------Arguments----------
参数:beta
Regression coefficient matrix
回归系数矩阵
参数:corPsi
Factor or indicator residual correlations.
因素或指标残余的相关性。
参数:totalVarPsi
Factor or indicator total variances. The default is that all factor or indicator total variances are 1.
因素或指标总方差。默认值是所有的因素或指标总方差为1。
值----------Value----------
A vector of factor (indicator) residual variances
一个向量的因素(指标)残留的差异
(作者)----------Author(s)----------
Sunthud Pornprasertmanit (University of Kansas; <a href="mailto:psunthud@ku.edu">psunthud@ku.edu</a>)
参见----------See Also----------
findIndIntercept to find indicator (measurement) intercepts
findIndIntercept找到指标(测量)拦截
findIndMean to find indicator (measurement) total means
findIndMean找到指标(测量)总装置
findIndResidualVar to find indicator (measurement) residual variances
findIndResidualVar找到指标(测量)残留的差异
findIndTotalVar to find indicator (measurement) total variances
findIndTotalVar找到指标(测量)总变异
findFactorIntercept to find factor intercepts
findFactorIntercept因素拦截
findFactorMean to find factor means
findFactorMean找到因素手段
findFactorTotalVar to find factor total variances
findFactorTotalVar找到因素总变异
findFactorTotalCov to find factor covariances
findFactorTotalCov因素的协方差
实例----------Examples----------
path <- matrix(0, 9, 9)
path[4, 1] <- path[7, 4] <- 0.6
path[5, 2] <- path[8, 5] <- 0.6
path[6, 3] <- path[9, 6] <- 0.6
path[5, 1] <- path[8, 4] <- 0.4
path[6, 2] <- path[9, 5] <- 0.4
facCor <- diag(9)
facCor[1, 2] <- facCor[2, 1] <- 0.4
facCor[1, 3] <- facCor[3, 1] <- 0.4
facCor[2, 3] <- facCor[3, 2] <- 0.4
totalVar <- rep(1, 9)
findFactorResidualVar(path, facCor, totalVar)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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