Standardization is used in many common methods in psychology to enhance the interpretability of results. For example, the so-called "betas" are usually reported in structural equation modeling (SEM). However, there are three situations in which standardization, as is usually conducted by SEM programs, makes the results difficult to interpret and sometimes even misleading: standardizing dummy variables, standardizing the product term in moderation, and standardizing a variable that is already measured on a meaningful unit. Another problem is the confidence interval of the standardized results: It is either not reported or computed using methods known to be biased or suboptimal. The R package betaselectr was developed to help users get standardized coefficients properly in the three situations above, along with appropriate standard errors and confidence intervals that take into account the sampling errors in the standard deviations used to do the standardization, and not only in structural equation modeling but also in multiple regression.
Sun et al. (Tue,) studied this question.