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We propose the effective use of security choice, a method considering duplicated resampling for the data to pick stable coefficients, to regularized SEM as a mechanism to overcome these limits. Across 2 simulation scientific studies, we realize that security choice significantly improves upon the LASSO in selecting the proper paths, specifically through decreasing the number of false positives. We nearby the content by showing the effective use of security selection in 2 empirical examples and presenting