Are dummy variables always 0 and 1?
Indeed, a dummy variable can take values either 1 or 0. It can express either a binary variable (for instance, man/woman, and it’s on you to decide which gender you encode to be 1 and which to be 0), or a categorical variables (for instance, level of education: basic/college/postgraduate).
Can dummy variables be less than 1?
Yes, coefficients of dummy variables can be more than one or less than zero. Remember that you can interpret that coefficient as the mean change in your response (dependent) variable when the dummy changes from 0 to 1, holding all other variables constant (i.e. ceteris paribus).
What do the numbers 1 and 0 mean for the variable female?
The number 1 and 0 have no numerical (quantitative) meaning. The two numbers are used to represent groups. Then a dummy variable can be defined as D = 1 for female and D = 0 for male. Such a dummy variable divides the sample into two subsamples (or two sub-populations): one for female and one for male.
Why are dummy variables important?
Dummy variables are useful because they enable us to use a single regression equation to represent multiple groups. This means that we don’t need to write out separate equation models for each subgroup. The dummy variables act like ‘switches’ that turn various parameters on and off in an equation.
What are the values of a dummy variable?
The values for a dummy variable do not have to be 0 and 1. Sometimes the values of a dummy variable are +1 and -1. In many analyses, such as dummy predictor variables in regression, you could actually use any two arbitrary values you want as codes for the dummy variable.
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.
When to use a dummy variable in logistic regression?
A dummy variable is used in logistic regression to answer questions for which there are only two (meaningful) outcomes. For example, suppose you which to check whether a tumor is cancerous enough to operate. This would be an example where using a dummy variable would be useful.
What does internally Stata do to a dummy variable?
Internally Stata will turn those variables in (a set of) 0/1 indicator (dummy) variables. The benefit of that is that the constant refers to conditional mean of the reference category.