I'm doing this, and it works. I know it has to have a name.
(background) I'm using a linear model (glm) and I get parameter estimates of various magnitude. My general formula is $ y = \alpha_1 \cdot x_1 ... + \alpha_n \cdot x_n + \epsilon $. Y is a binomial valued, and I am using logit-link.
(what I do) When I want to find parameters that, all else being equal, more strongly impact the variable of interest after fitting, I look at mean values of the measure, and multiply it by the parameter estimate. That is to say, the fit gives me the $\alpha_i$ values then I find the product $\alpha_i \cdot E\left(x_i\right)$ and use them to compare strength of $x_i$ on $y$.
What is the proper term for what I am doing?
I am tempted to use words like "importance", "leverage", "significance" or "impact" but those all have very narrowly defined meanings that might not necessarily apply here.