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I want to run some comparisons of a quantity between different populations. Such quantity comes from a model that includes, among other variables, the variable age. So, one of the variables affecting such quantity is age. I want to account for the different age distribution in the the populations in order to obtain meaningful comparisons. I found this wikipedia article that discusses Age Adjustment

https://en.wikipedia.org/wiki/Age_adjustment

However, the papers presented in the references are a bit old or do not seem to have attracted much attention among practitioners.

I was wondering what is a good reference to identify gold-standard methods (i.e. widely accepted) or the state-of-the-art in age standardization/adjustment methods?

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You can do an ANCOVA (Analysis of Covariance). You can just include the Age as an Covariate, so this will "take out" the effects of age. An will result in a model which evaluates the difference between group as if all were the same age.

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  • $\begingroup$ I am afraid this is incorrect. Including the variable in the models does not correct for different distributions of age in the two populations. This is indeed the motivation for using age adjustment methods. $\endgroup$
    – Compare
    Commented Mar 1, 2022 at 12:54

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