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So we can control for some of that, but we can't control for it perfectly.
Although you can control for these in analyses, you can never be sure you've adequately adjusted for them.
You can control for that by looking at the employment-to-population ratio for each bracket.
Let me see whether I can control for that by actually not making the coins say heads or tails.
First, using data on 500,000 randomly sampled Americans and West Europeans, the paper designs a test that can control for cohort effects.
Supposing executive effort needs to scale 1-to-1 with other inputs (capital, labor), we can control for expenditures on these other inputs to see if that explains the changes in executive pay.
Greater diversity within research communities can control for bias in this process.
Fortunately, as Alice Eagly points out in her analysis, there are sophisticated statistical techniques that can control for these issues.
By taking advantage of the panel structure of our data, we can control for time-invariant unobserved individual characteristics.
While the analyst can control for the former using standard multivariate regression analysis, less can be done about the latter.
Because the problem with pointing it at violent film and violent video games is that we can control for that on a global scale.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com