psych (version 1.0-88)

smc: Find the Squared Multiple Correlation (SMC) of each variable with the remaining variables in a matrix

Description

The squared multiple correlation of a variable with the remaining variables in a matrix is sometimes used as initial estimates of the communality of a variable.

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.

Usage

smc(R,covar=FALSE)

Arguments

R

A correlation matrix or a dataframe. In the latter case, correlations are found.

covar

if covar = TRUE and R is either a covariance matrix or data frame, then return the smc * variance for each item

Value

• a vector of squared multiple correlations. Or, if covar=TRUE, a vector of squared multiple correlations * the item variances

  If the matrix is not invertible, then a vector of 1s is returned

See Also

mat.regress, factor.pa

Examples

R <- make.hierarchical()
round(smc(R),2)