A Simple Approach for Estimating Parameters in a Linear Structural Equation Model

Popularly used iterative algorithms, such as maximum likelihood estimation, is limited in estimating the linear structural equation model. We suggest a non-iterative approach motivated by partial least squares regression. This approach is applied to a real dataset from a study of customer satisfaction index model is Shanghai. The application evidence the validation and the efficiency of our propose approach.