SMCs are also used when estimating reliability using Guttman's lambda 6 guttman
coefficient.
The SMC is just 1 - 1/diag(R.inv) where R.inv is the inverse of R.
smc(R,covar=FALSE)
If the matrix is not invertible, then a vector of 1s is returned.
In the case of correlation or covariance matrices with some NAs, those variables with NAs are dropped and the SMC for the remaining variables are found. The missing SMCs are then estimated by finding the maximum correlation for that column (with a warning).
mat.regress
, fa
R <- make.hierarchical()
round(smc(R),2)
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