# Which logistic model should I use in Stata when I have a mix of categorical and scalar variables?

I want to run a regression in Stata. The dependent variable is a scalar categorical variable indicating life satisfaction ls (1= satisfied, 2= intermediate, 3= dissatisfied).

The independent variables are as follows:

entrep = if the person is an entrepreneur (1 if yes, 0 if no)

edu = level of education (1 if primary, 2 if high school, 3 if university degree)

sex = (1 if male, 0 if female)

marital = marital status (1 if single, 2 if married, 3 if divorced, 4 if widowed, 5 if remarried, 6 if cohabiting)

extro = scale for personality characteristic of extroversion (range between 0-9, 9 having highest level). This variable is based on several questions and can be a decimal.

neuro = scale for personality characteristic of neuroticism (range between 0-10, 10 having highest level). This variable is based on several questions and can be a decimal.

Since I have a mix of categorical and scalar variables, my question is which model should I use and how exactly can I do it in Stata?

How to do this in Stata is off-limits here, but can be determined within about a minute by looking at the documentation or using search. See https://stats.stackexchange.com/help/on-topic for more advice on software-related questions.