smc {psych} R Documentation

## 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

### Author(s)

William Revelle

`mat.regress`, `fa`
```R <- make.hierarchical()