Principal component analysis (PCA) is a widely used method for factor extraction, which is the first phase of EFA.[1] Factor weights are computed to extract the maximum possible variance, with successive factoring continuing until there is no further meaningful variance left.[10] The factor model must then be rotated for analysis.[10]