Let's be clear: standardizing variables will have no impact on any properly done interpretations of any kind of regression model. Standardizing is just a combination of centering and rescaling. So standardizing variables should be done when, and only when, the standardized variable is easier to understand than the unstandardized one. This occurs primarily, if not exclusively, with interval-level measurements that have only arbitrary units. When a measurement has meaningful units of its own, standardization just obfuscates the findings. In the end, of course, it is possible to de-obfuscate the findings that come with the use of standardized variables by inverting the standardization process on the results (if you have access to the data so that you can find out the appropriate means and standard deviations to use). And anyone who takes the trouble to do this will reach the same conclusions that would be reached with analysis of unstandardized variables. But this approach is antithetical to the basic premise of research, wherein we are trying to clarify things and explain them in terms that are easily comprehensible to our intended audience, not to put obstacles in their path.
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