小样本下岭PLS-SEM与岭CB-SEM的比较OA北大核心CHSSCDCSSCICSTPCD

There are two main structural equation modeling:CB-SEM(covariance-based SEM)and PLS-SEM(partial least squares SEM).When the sample size is small,the CB-SEM method often fails to converge,which can be improved by using ridge method.This paper mainly studies the application of ridge method to PLS-SEM,and compares the performance of PLS-SEM and CB-SEM under ridge method.The research shows that CB-SEM and PLS-SEM estimators are generally more accurate than con-ventional CB-SEM and PLS-SEM estimators,but the bias has not been significantly improved.The estimation accuracy of PLS-SEM and ridge PLS-SEM is better than that of CB-SEM and ridge CB-SEM under small samples.For endogenous latent variables affected by intermediate variables,ridge PLS-SEM is the most accurate in estimating the influence(path coefficient)of other latent variables.