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library(lavaan)
This is lavaan 0.6-19
lavaan is FREE software! Please report any bugs.
If you have an article with the correlations and standard deviations for your variables you can convert that to a covariance matrix with the following code. You can then take the resulting covariance matrix and copy it into lavaan code for your model (see block 3)
# Example correlation matrixcorrelation_matrix <-matrix(c(1, 0.8, 0.6,0.8, 1, 0.7,0.6, 0.7, 1), nrow =3, byrow =TRUE)# Standard deviations for the variablesstd_devs <-c(2, 3, 4)# Transform correlation matrix to covariance matrixcovariance_matrix <- correlation_matrix * (std_devs %*%t(std_devs))# Create a mask for the lower triangular partlower_half <- covariance_matrixlower_half[upper.tri(covariance_matrix)] <-""# Use NA or 0 if you prefer# Print the lower halfprint(lower_half, quote =FALSE)
[,1] [,2] [,3]
[1,] 4
[2,] 4.8 9
[3,] 4.8 8.4 16
Once you have your covariance matrix you can past it in as shown below (this is a different data set which has a known SEM model, but to get it you would use the step shown in block 2 above)
Next you specify the model just as you would as if you had the full raw data. The only difference is that when you are specifying your fit object (i.e., fit) instead of using the data arguement you use “sample.cov = covariance object name” and the “sample.nobs = sample size”