On the Computation of the Correlation Matrix Implied by a Recursive Path Model

Abstract

Path Analysis is a powerful technique to examine the relationships of cause and effect between several phenomena presented as variables. One of its major steps is the computation of the correlation matrix implied by the model. This matrix is useful to estimate parameters as well as to assess the overall fit of the model. In this paper, the concept of the implied correlation matrix is introduced. Besides, two major methods used for its computation are discussed. Finally, comparisons between these methods in terms of hypotheses and with simulated example using Python are proposed.