Let's say the mean income in New Jersey (group 1) and Florida (group 2) is $80,000 and $55,000 respectively. Using a dataset of relevant predictor variables, I'd like to attempt to explain this gap (i.e. $25,000). My question is what method I'd use to do so. For example, would I take the difference of the means and estimate a regression with it as my DV? Thanks in advance!
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Assuming you are using continuous independent variables to explain the difference, you can use a linear regression of the form:
$$y\sim\beta_1 + \beta_2 x + z_1(\beta_3+\beta_4 x)$$,
where y is your income, $z_1$ is an indicator variable for whether a subject is in group 2, and $x$ is your covariate independent variable. When you fit this model, significance of $\beta_3$ will tell you if there is a difference in the two group's intercept, and significance of $\beta_4$ will tell you if your covariate contribute to the observed difference in group incomes.
Asy
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Also see this post about the equivalence between regression and t-test/ANOVA
– Asy Feb 10 '18 at 06:06