Rasin R S : Like Marcel Grieger , I have not seen this index in the context of confirmatory factor analysis (CFA).
What do you mean by "most influenced"? Often, we use standardized path (structural regression) coefficients to examine relative "influence" in structural equation (regression) and path models. You can also compute "total effects" in such models as the sum of the direct plus all indirect effects. In addition, R^2 values can be computed to estimate "total variability accounted for" in a given endogenous variable/ dependent factor. But I'm not sure this is what you have in mind.
Pratt’s index was calculated using the correlation between the criterion variable and the specific independent variable (IV), R2 value, and standardized regression coefficient of the specific IV in multiple regression analysis to provide information about the percentage of explained variance of the IV in the R2 value (Wu, Zumbo, & Marshall, 2014). Although this index initially developed for multiple regression analysis, subsequent studies extended its utility for exploratory and confirmatory factor analysis. Thus, this index may be used in exploratory factor analysis and confirmatory factor analysis to determine item importance in latent variable.
However, as indicated by Dr.Christian Geiser, their utility in these analyses still scarce as well as software for these analyses except for R software.
For more information, see below articles.
Wu, A. D., & Zumbo, B. D. (2017). Using Pratt's Importance Measures in confirmatory factor analyses. Journal of Modern Applied Statistical Methods, 16(2), 81-98.
Wu, A. D., Zumbo, B. D., & Marshall, S. K. (2014). A method to aid in the interpretation of EFA results: An application of Pratt’s measures. International Journal of Behavioral Development, 38(1), 98-110.