# Confirmatory factor analysis without the raw data

I have the correlation matrix, sample sizes, and descriptive statistics for a set of variables. I know that it is possible to run principal component analysis (PCA) and exploratory factor analysis (EFA) just using the correlation matrix, but is it possible to do confirmatory factor analysis (CFA) and structural equation modelling (SEM) using just this matrix as well?

If you use R, I suggest you use the lavaan package. See this tutorial page for using a covariance matrix as input. You need to compute a covariance matrix from your correlation matrix and descriptive statistics (i.e., standard deviations) first. You can also use the sem package.