I'm wondering about how to calculate predicted probabilities using a binary logistic regression model when one or more of the variables in the model is unknown.

For example, say I built a model to determine whether or not someone will own a car which uses the following:

- Age, where the outcome is 0 = over 25 years of age, 1 = below 25

- Gender, where 0 = male, 1 = female

- Home proximity to work where the outcome is divided categorically, 0= less than 10 km, 1 = 10-30 km, 2 = over 30 km

- Household income, where 0 = 0- $30,000 , 1 = $30,000 - $60,000, 3 = $Over 60,000

Now, if someone asks me to calculate the predicted probability for someone owning a car given their age, gender, and income, yet they want to know without specifying home proximity. Can this be accomplished? Can I use my model to predict this outcome holding home proximity constant?

Would I also be able to do a predicted probability when more than one variable is missing (say home proximity and gender)?

Thank you in advance!