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How do you interpret the coefficient of dummy variables?
The coefficient on a dummy variable with a log-transformed Y variable is interpreted as the percentage change in Y associated with having the dummy variable characteristic relative to the omitted category, with all other included X variables held fixed.
How do you read interaction terms?
To understand potential interaction effects, compare the lines from the interaction plot:
- If the lines are parallel, there is no interaction.
- If the lines are not parallel, there is an interaction.
How does interaction between two dummy variables affect a regression?
Whereas in the regression, if the interaction term is correlated with the two dummy variables, it can affect the estimate (and resulting p values) of the main effect of the two dummy variables (and the interaction term also).
Can a male dummy variable be used as an intercept variable?
Now introduce a male dummy variable (1= male, 0 otherwise) as an intercept dummy. This specification says the slope effect (of age) is the same for men and women, but that the intercept (or the average difference in pay between men and women) is different.
How to calculate the interaction between dummy coded categorical?
Always start with the constant and then add to it any of the factors that belong to it. So we’ll need to add to the constant the value of being married, of being male and also the extra value for being married and male: 41.7 + 4.3 – 1.9 + 3.6 = 47.7.
When to center a variable in a dummy predictor?
If you are creating a dummy predictor by continuous predictor interaction it is a good idea to center the continuous variable if “0” is not within the range of the observed values for the continuous predictor. However, if you rely upon the results from the emmeans or margins command output to explain your results then centering is not important.